-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
0.62
0.6217694 = product of:
0.7461233 = sum of:
0.23284428 = weight(_text_:umfeld in 2134) [ClassicSimilarity], result of:
0.23284428 = score(doc=2134,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.86918265 = fieldWeight in 2134, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.0136442585 = weight(_text_:in in 2134) [ClassicSimilarity], result of:
0.0136442585 = score(doc=2134,freq=2.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.21040362 = fieldWeight in 2134, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.21327409 = weight(_text_:indexierung in 2134) [ClassicSimilarity], result of:
0.21327409 = score(doc=2134,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.8318544 = fieldWeight in 2134, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.0790651 = weight(_text_:u in 2134) [ClassicSimilarity], result of:
0.0790651 = score(doc=2134,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.50648975 = fieldWeight in 2134, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.20729557 = sum of:
0.116868265 = weight(_text_:retrieval in 2134) [ClassicSimilarity], result of:
0.116868265 = score(doc=2134,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.8104139 = fieldWeight in 2134, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.09042731 = weight(_text_:22 in 2134) [ClassicSimilarity], result of:
0.09042731 = score(doc=2134,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.5416616 = fieldWeight in 2134, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.109375 = fieldNorm(doc=2134)
0.8333333 = coord(5/6)
- Date
- 30. 3.2001 13:32:22
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998)
0.30
0.30194896 = product of:
0.36233878 = sum of:
0.11642214 = weight(_text_:umfeld in 1319) [ClassicSimilarity], result of:
0.11642214 = score(doc=1319,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.43459132 = fieldWeight in 1319, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.0068221292 = weight(_text_:in in 1319) [ClassicSimilarity], result of:
0.0068221292 = score(doc=1319,freq=2.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.10520181 = fieldWeight in 1319, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.106637046 = weight(_text_:indexierung in 1319) [ClassicSimilarity], result of:
0.106637046 = score(doc=1319,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.4159272 = fieldWeight in 1319, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.03953255 = weight(_text_:u in 1319) [ClassicSimilarity], result of:
0.03953255 = score(doc=1319,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.25324488 = fieldWeight in 1319, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.09292492 = sum of:
0.047711264 = weight(_text_:retrieval in 1319) [ClassicSimilarity], result of:
0.047711264 = score(doc=1319,freq=4.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.33085006 = fieldWeight in 1319, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.045213655 = weight(_text_:22 in 1319) [ClassicSimilarity], result of:
0.045213655 = score(doc=1319,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.2708308 = fieldWeight in 1319, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.8333333 = coord(5/6)
- Date
- 1. 8.1996 22:08:06
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Srinivasan, P.: Query expansion and MEDLINE (1996)
0.29
0.29250756 = product of:
0.35100907 = sum of:
0.13305387 = weight(_text_:umfeld in 8453) [ClassicSimilarity], result of:
0.13305387 = score(doc=8453,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.4966758 = fieldWeight in 8453, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0625 = fieldNorm(doc=8453)
0.007796719 = weight(_text_:in in 8453) [ClassicSimilarity], result of:
0.007796719 = score(doc=8453,freq=2.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.120230645 = fieldWeight in 8453, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0625 = fieldNorm(doc=8453)
0.12187091 = weight(_text_:indexierung in 8453) [ClassicSimilarity], result of:
0.12187091 = score(doc=8453,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.47534537 = fieldWeight in 8453, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0625 = fieldNorm(doc=8453)
0.045180056 = weight(_text_:u in 8453) [ClassicSimilarity], result of:
0.045180056 = score(doc=8453,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.28942272 = fieldWeight in 8453, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0625 = fieldNorm(doc=8453)
0.04310751 = product of:
0.08621502 = sum of:
0.08621502 = weight(_text_:retrieval in 8453) [ClassicSimilarity], result of:
0.08621502 = score(doc=8453,freq=10.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.59785134 = fieldWeight in 8453, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=8453)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Kulyukin, V.A.; Settle, A.: Ranked retrieval with semantic networks and vector spaces (2001)
0.29
0.29090765 = product of:
0.3490892 = sum of:
0.13305387 = weight(_text_:umfeld in 6934) [ClassicSimilarity], result of:
0.13305387 = score(doc=6934,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.4966758 = fieldWeight in 6934, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0625 = fieldNorm(doc=6934)
0.015593438 = weight(_text_:in in 6934) [ClassicSimilarity], result of:
0.015593438 = score(doc=6934,freq=8.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.24046129 = fieldWeight in 6934, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0625 = fieldNorm(doc=6934)
0.12187091 = weight(_text_:indexierung in 6934) [ClassicSimilarity], result of:
0.12187091 = score(doc=6934,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.47534537 = fieldWeight in 6934, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0625 = fieldNorm(doc=6934)
0.045180056 = weight(_text_:u in 6934) [ClassicSimilarity], result of:
0.045180056 = score(doc=6934,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.28942272 = fieldWeight in 6934, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0625 = fieldNorm(doc=6934)
0.03339093 = product of:
0.06678186 = sum of:
0.06678186 = weight(_text_:retrieval in 6934) [ClassicSimilarity], result of:
0.06678186 = score(doc=6934,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.46309367 = fieldWeight in 6934, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=6934)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- The equivalence of semantic networks with spreading activation and vector spaces with dot product is investigated under ranked retrieval. Semantic networks are viewed as networks of concepts organized in terms of abstraction and packaging relations. It is shown that the two models can be effectively constructed from each other. A formal method is suggested to analyze the models in terms of their relative performance in the same universe of objects
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
0.28
0.2765331 = product of:
0.3318397 = sum of:
0.09979041 = weight(_text_:umfeld in 2419) [ClassicSimilarity], result of:
0.09979041 = score(doc=2419,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 2419, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.013075498 = weight(_text_:in in 2419) [ClassicSimilarity], result of:
0.013075498 = score(doc=2419,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.20163295 = fieldWeight in 2419, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.09140319 = weight(_text_:indexierung in 2419) [ClassicSimilarity], result of:
0.09140319 = score(doc=2419,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 2419, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.047920685 = weight(_text_:u in 2419) [ClassicSimilarity], result of:
0.047920685 = score(doc=2419,freq=4.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.30697915 = fieldWeight in 2419, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.07964993 = sum of:
0.040895373 = weight(_text_:retrieval in 2419) [ClassicSimilarity], result of:
0.040895373 = score(doc=2419,freq=4.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.2835858 = fieldWeight in 2419, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.03875456 = weight(_text_:22 in 2419) [ClassicSimilarity], result of:
0.03875456 = score(doc=2419,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.23214069 = fieldWeight in 2419, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.8333333 = coord(5/6)
- Abstract
- The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
- Date
- 16.11.2008 16:22:48
- Series
- Lecture notes in computer science; vol.3232
- Source
- Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Beaulieu, M.; Jones, S.: Interactive searching and interface issues in the Okapi best match probabilistic retrieval system (1998)
0.26
0.26297128 = product of:
0.31556556 = sum of:
0.11642214 = weight(_text_:umfeld in 430) [ClassicSimilarity], result of:
0.11642214 = score(doc=430,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.43459132 = fieldWeight in 430, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0546875 = fieldNorm(doc=430)
0.015254747 = weight(_text_:in in 430) [ClassicSimilarity], result of:
0.015254747 = score(doc=430,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.23523843 = fieldWeight in 430, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0546875 = fieldNorm(doc=430)
0.106637046 = weight(_text_:indexierung in 430) [ClassicSimilarity], result of:
0.106637046 = score(doc=430,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.4159272 = fieldWeight in 430, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0546875 = fieldNorm(doc=430)
0.03953255 = weight(_text_:u in 430) [ClassicSimilarity], result of:
0.03953255 = score(doc=430,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.25324488 = fieldWeight in 430, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0546875 = fieldNorm(doc=430)
0.03771907 = product of:
0.07543814 = sum of:
0.07543814 = weight(_text_:retrieval in 430) [ClassicSimilarity], result of:
0.07543814 = score(doc=430,freq=10.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.5231199 = fieldWeight in 430, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=430)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Robertson, S.E.: OKAPI at TREC-3 (1995)
0.25
0.25121394 = product of:
0.30145675 = sum of:
0.11642214 = weight(_text_:umfeld in 5694) [ClassicSimilarity], result of:
0.11642214 = score(doc=5694,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.43459132 = fieldWeight in 5694, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0546875 = fieldNorm(doc=5694)
0.009647949 = weight(_text_:in in 5694) [ClassicSimilarity], result of:
0.009647949 = score(doc=5694,freq=4.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.14877784 = fieldWeight in 5694, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0546875 = fieldNorm(doc=5694)
0.106637046 = weight(_text_:indexierung in 5694) [ClassicSimilarity], result of:
0.106637046 = score(doc=5694,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.4159272 = fieldWeight in 5694, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0546875 = fieldNorm(doc=5694)
0.03953255 = weight(_text_:u in 5694) [ClassicSimilarity], result of:
0.03953255 = score(doc=5694,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.25324488 = fieldWeight in 5694, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0546875 = fieldNorm(doc=5694)
0.029217066 = product of:
0.058434132 = sum of:
0.058434132 = weight(_text_:retrieval in 5694) [ClassicSimilarity], result of:
0.058434132 = score(doc=5694,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.40520695 = fieldWeight in 5694, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=5694)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Hancock-Beaulieu, M.; Walker, S.: ¬An evaluation of automatic query expansion in an online library catalogue (1992)
0.25
0.2455958 = product of:
0.29471496 = sum of:
0.11642214 = weight(_text_:umfeld in 2731) [ClassicSimilarity], result of:
0.11642214 = score(doc=2731,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.43459132 = fieldWeight in 2731, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0546875 = fieldNorm(doc=2731)
0.015254747 = weight(_text_:in in 2731) [ClassicSimilarity], result of:
0.015254747 = score(doc=2731,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.23523843 = fieldWeight in 2731, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0546875 = fieldNorm(doc=2731)
0.106637046 = weight(_text_:indexierung in 2731) [ClassicSimilarity], result of:
0.106637046 = score(doc=2731,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.4159272 = fieldWeight in 2731, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0546875 = fieldNorm(doc=2731)
0.03953255 = weight(_text_:u in 2731) [ClassicSimilarity], result of:
0.03953255 = score(doc=2731,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.25324488 = fieldWeight in 2731, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0546875 = fieldNorm(doc=2731)
0.016868481 = product of:
0.033736963 = sum of:
0.033736963 = weight(_text_:retrieval in 2731) [ClassicSimilarity], result of:
0.033736963 = score(doc=2731,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.23394634 = fieldWeight in 2731, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=2731)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- An automatic query expansion (AQE) facility in anonline catalogue was evaluated in an operational library setting. The OKAPI experimental system had other features including: ranked output 'best match' keyword searching, automatic stemming, spelling normalisation and cross referencing as well as relevance feedback. A combination of transaction log analysis, search replays, questionnaires and interviews was used for data collection. Findings show that contrary to previous results, AQE was beneficial in a substantial number of searches. Use intentions, the effectiveness of the 'best match' search and user interaction were identified as the main factors affecting the take-up of the query expansion facility
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007)
0.24
0.24425372 = product of:
0.29310447 = sum of:
0.11642214 = weight(_text_:umfeld in 919) [ClassicSimilarity], result of:
0.11642214 = score(doc=919,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.43459132 = fieldWeight in 919, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0546875 = fieldNorm(doc=919)
0.0136442585 = weight(_text_:in in 919) [ClassicSimilarity], result of:
0.0136442585 = score(doc=919,freq=8.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.21040362 = fieldWeight in 919, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0546875 = fieldNorm(doc=919)
0.106637046 = weight(_text_:indexierung in 919) [ClassicSimilarity], result of:
0.106637046 = score(doc=919,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.4159272 = fieldWeight in 919, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0546875 = fieldNorm(doc=919)
0.03953255 = weight(_text_:u in 919) [ClassicSimilarity], result of:
0.03953255 = score(doc=919,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.25324488 = fieldWeight in 919, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0546875 = fieldNorm(doc=919)
0.016868481 = product of:
0.033736963 = sum of:
0.033736963 = weight(_text_:retrieval in 919) [ClassicSimilarity], result of:
0.033736963 = score(doc=919,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.23394634 = fieldWeight in 919, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=919)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- This paper examines the meaning of context in relation to ontology based query expansion and contains a review of query expansion approaches. The various query expansion approaches include relevance feedback, corpus dependent knowledge models and corpus independent knowledge models. Case studies detailing query expansion using domain-specific and domain-independent ontologies are also included. The penultimate section attempts to synthesise the information obtained from the review and provide success factors in using an ontology for query expansion. Finally the area of further research in applying context from an ontology to query expansion within a newswire domain is described.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003)
0.23
0.22794658 = product of:
0.2735359 = sum of:
0.08315867 = weight(_text_:umfeld in 1428) [ClassicSimilarity], result of:
0.08315867 = score(doc=1428,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 1428, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.01193624 = weight(_text_:in in 1428) [ClassicSimilarity], result of:
0.01193624 = score(doc=1428,freq=12.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.18406484 = fieldWeight in 1428, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.07616932 = weight(_text_:indexierung in 1428) [ClassicSimilarity], result of:
0.07616932 = score(doc=1428,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 1428, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.028237537 = weight(_text_:u in 1428) [ClassicSimilarity], result of:
0.028237537 = score(doc=1428,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 1428, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.07403414 = sum of:
0.041738667 = weight(_text_:retrieval in 1428) [ClassicSimilarity], result of:
0.041738667 = score(doc=1428,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.28943354 = fieldWeight in 1428, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.03229547 = weight(_text_:22 in 1428) [ClassicSimilarity], result of:
0.03229547 = score(doc=1428,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.19345059 = fieldWeight in 1428, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=1428)
0.8333333 = coord(5/6)
- Abstract
- Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.
- Date
- 22. 3.2003 19:35:46
- Footnote
- Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Nie, J.-Y.: Query expansion and query translation as logical inference (2003)
0.22
0.2193311 = product of:
0.26319733 = sum of:
0.09979041 = weight(_text_:umfeld in 1425) [ClassicSimilarity], result of:
0.09979041 = score(doc=1425,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 1425, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=1425)
0.013075498 = weight(_text_:in in 1425) [ClassicSimilarity], result of:
0.013075498 = score(doc=1425,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.20163295 = fieldWeight in 1425, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=1425)
0.09140319 = weight(_text_:indexierung in 1425) [ClassicSimilarity], result of:
0.09140319 = score(doc=1425,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 1425, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=1425)
0.033885043 = weight(_text_:u in 1425) [ClassicSimilarity], result of:
0.033885043 = score(doc=1425,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.21706703 = fieldWeight in 1425, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=1425)
0.0250432 = product of:
0.0500864 = sum of:
0.0500864 = weight(_text_:retrieval in 1425) [ClassicSimilarity], result of:
0.0500864 = score(doc=1425,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.34732026 = fieldWeight in 1425, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=1425)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- A number of studies have examined the problems of query expansion in monolingual Information Retrieval (IR), and query translation for crosslanguage IR. However, no link has been made between them. This article first shows that query translation is a special case of query expansion. There is also another set of studies an inferential IR. Again, there is no relationship established with query translation or query expansion. The second claim of this article is that logical inference is a general form that covers query expansion and query translation. This analysis provides a unified view of different subareas of IR. We further develop the inferential IR approach in two particular contexts: using fuzzy logic and probability theory. The evaluation formulas obtained are shown to strongly correspond to those used in other IR models. This indicates that inference is indeed the core of advanced IR.
- Footnote
- Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995)
0.22
0.21855475 = product of:
0.2622657 = sum of:
0.09979041 = weight(_text_:umfeld in 5696) [ClassicSimilarity], result of:
0.09979041 = score(doc=5696,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 5696, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=5696)
0.00826967 = weight(_text_:in in 5696) [ClassicSimilarity], result of:
0.00826967 = score(doc=5696,freq=4.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.12752387 = fieldWeight in 5696, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=5696)
0.09140319 = weight(_text_:indexierung in 5696) [ClassicSimilarity], result of:
0.09140319 = score(doc=5696,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 5696, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=5696)
0.033885043 = weight(_text_:u in 5696) [ClassicSimilarity], result of:
0.033885043 = score(doc=5696,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.21706703 = fieldWeight in 5696, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=5696)
0.028917395 = product of:
0.05783479 = sum of:
0.05783479 = weight(_text_:retrieval in 5696) [ClassicSimilarity], result of:
0.05783479 = score(doc=5696,freq=8.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.40105087 = fieldWeight in 5696, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=5696)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014)
0.22
0.21532625 = product of:
0.2583915 = sum of:
0.09979041 = weight(_text_:umfeld in 2799) [ClassicSimilarity], result of:
0.09979041 = score(doc=2799,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 2799, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=2799)
0.00826967 = weight(_text_:in in 2799) [ClassicSimilarity], result of:
0.00826967 = score(doc=2799,freq=4.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.12752387 = fieldWeight in 2799, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=2799)
0.09140319 = weight(_text_:indexierung in 2799) [ClassicSimilarity], result of:
0.09140319 = score(doc=2799,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 2799, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=2799)
0.033885043 = weight(_text_:u in 2799) [ClassicSimilarity], result of:
0.033885043 = score(doc=2799,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.21706703 = fieldWeight in 2799, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=2799)
0.0250432 = product of:
0.0500864 = sum of:
0.0500864 = weight(_text_:retrieval in 2799) [ClassicSimilarity], result of:
0.0500864 = score(doc=2799,freq=6.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.34732026 = fieldWeight in 2799, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=2799)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995)
0.21
0.21478468 = product of:
0.25774163 = sum of:
0.08315867 = weight(_text_:umfeld in 5697) [ClassicSimilarity], result of:
0.08315867 = score(doc=5697,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 5697, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.0137827825 = weight(_text_:in in 5697) [ClassicSimilarity], result of:
0.0137827825 = score(doc=5697,freq=16.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.21253976 = fieldWeight in 5697, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.07616932 = weight(_text_:indexierung in 5697) [ClassicSimilarity], result of:
0.07616932 = score(doc=5697,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 5697, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.028237537 = weight(_text_:u in 5697) [ClassicSimilarity], result of:
0.028237537 = score(doc=5697,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 5697, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.0563933 = sum of:
0.02409783 = weight(_text_:retrieval in 5697) [ClassicSimilarity], result of:
0.02409783 = score(doc=5697,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.16710453 = fieldWeight in 5697, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.03229547 = weight(_text_:22 in 5697) [ClassicSimilarity], result of:
0.03229547 = score(doc=5697,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.19345059 = fieldWeight in 5697, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=5697)
0.8333333 = coord(5/6)
- Abstract
- The performance of 8 ranking algorithms was evaluated with respect to their effectiveness in ranking terms for query expansion. The evaluation was conducted within an investigation of interactive query expansion and relevance feedback in a real operational environment. Focuses on the identification of algorithms that most effectively take cognizance of user preferences. user choices (i.e. the terms selected by the searchers for the query expansion search) provided the yardstick for the evaluation of the 8 ranking algorithms. This methodology introduces a user oriented approach in evaluating ranking algorithms for query expansion in contrast to the standard, system oriented approaches. Similarities in the performance of the 8 algorithms and the ways these algorithms rank terms were the main focus of this evaluation. The findings demonstrate that the r-lohi, wpq, enim, and porter algorithms have similar performance in bringing good terms to the top of a ranked list of terms for query expansion. However, further evaluation of the algorithms in different (e.g. full text) environments is needed before these results can be generalized beyond the context of the present study
- Date
- 22. 2.1996 13:14:10
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006)
0.21
0.21237925 = product of:
0.2548551 = sum of:
0.08315867 = weight(_text_:umfeld in 56) [ClassicSimilarity], result of:
0.08315867 = score(doc=56,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 56, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.010896247 = weight(_text_:in in 56) [ClassicSimilarity], result of:
0.010896247 = score(doc=56,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.16802745 = fieldWeight in 56, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.07616932 = weight(_text_:indexierung in 56) [ClassicSimilarity], result of:
0.07616932 = score(doc=56,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 56, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.028237537 = weight(_text_:u in 56) [ClassicSimilarity], result of:
0.028237537 = score(doc=56,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 56, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.0563933 = sum of:
0.02409783 = weight(_text_:retrieval in 56) [ClassicSimilarity], result of:
0.02409783 = score(doc=56,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.16710453 = fieldWeight in 56, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.03229547 = weight(_text_:22 in 56) [ClassicSimilarity], result of:
0.03229547 = score(doc=56,freq=2.0), product of:
0.16694428 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047673445 = queryNorm
0.19345059 = fieldWeight in 56, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.8333333 = coord(5/6)
- Abstract
- The study reported here investigated the query expansion behavior of end-users interacting with a thesaurus-enhanced search system on the Web. Two groups, namely academic staff and postgraduate students, were recruited into this study. Data were collected from 90 searches performed by 30 users using the OVID interface to the CAB abstracts database. Data-gathering techniques included questionnaires, screen capturing software, and interviews. The results presented here relate to issues of search-topic and search-term characteristics, number and types of expanded queries, usefulness of thesaurus terms, and behavioral differences between academic staff and postgraduate students in their interaction. The key conclusions drawn were that (a) academic staff chose more narrow and synonymous terms than did postgraduate students, who generally selected broader and related terms; (b) topic complexity affected users' interaction with the thesaurus in that complex topics required more query expansion and search term selection; (c) users' prior topic-search experience appeared to have a significant effect on their selection and evaluation of thesaurus terms; (d) in 50% of the searches where additional terms were suggested from the thesaurus, users stated that they had not been aware of the terms at the beginning of the search; this observation was particularly noticeable in the case of postgraduate students.
- Date
- 22. 7.2006 16:32:43
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Zhang, W.; Yoshida, T.; Tang, X.: ¬A comparative study of TF*IDF, LSI and multi-words for text classification (2011)
0.21
0.21155068 = product of:
0.25386083 = sum of:
0.09979041 = weight(_text_:umfeld in 1165) [ClassicSimilarity], result of:
0.09979041 = score(doc=1165,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 1165, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=1165)
0.014323489 = weight(_text_:in in 1165) [ClassicSimilarity], result of:
0.014323489 = score(doc=1165,freq=12.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.22087781 = fieldWeight in 1165, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=1165)
0.09140319 = weight(_text_:indexierung in 1165) [ClassicSimilarity], result of:
0.09140319 = score(doc=1165,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 1165, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=1165)
0.033885043 = weight(_text_:u in 1165) [ClassicSimilarity], result of:
0.033885043 = score(doc=1165,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.21706703 = fieldWeight in 1165, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=1165)
0.014458697 = product of:
0.028917395 = sum of:
0.028917395 = weight(_text_:retrieval in 1165) [ClassicSimilarity], result of:
0.028917395 = score(doc=1165,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.20052543 = fieldWeight in 1165, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=1165)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- One of the main themes in text mining is text representation, which is fundamental and indispensable for text-based intellegent information processing. Generally, text representation inludes two tasks: indexing and weighting. This paper has comparatively studied TF*IDF, LSI and multi-word for text representation. We used a Chinese and an English document collection to respectively evaluate the three methods in information retreival and text categorization. Experimental results have demonstrated that in text categorization, LSI has better performance than other methods in both document collections. Also, LSI has produced the best performance in retrieving English documents. This outcome has shown that LSI has both favorable semantic and statistical quality and is different with the claim that LSI can not produce discriminative power for indexing.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998)
0.21
0.20936035 = product of:
0.25123242 = sum of:
0.09979041 = weight(_text_:umfeld in 5704) [ClassicSimilarity], result of:
0.09979041 = score(doc=5704,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.37250686 = fieldWeight in 5704, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.046875 = fieldNorm(doc=5704)
0.011695079 = weight(_text_:in in 5704) [ClassicSimilarity], result of:
0.011695079 = score(doc=5704,freq=8.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.18034597 = fieldWeight in 5704, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=5704)
0.09140319 = weight(_text_:indexierung in 5704) [ClassicSimilarity], result of:
0.09140319 = score(doc=5704,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.35650903 = fieldWeight in 5704, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.046875 = fieldNorm(doc=5704)
0.033885043 = weight(_text_:u in 5704) [ClassicSimilarity], result of:
0.033885043 = score(doc=5704,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.21706703 = fieldWeight in 5704, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=5704)
0.014458697 = product of:
0.028917395 = sum of:
0.028917395 = weight(_text_:retrieval in 5704) [ClassicSimilarity], result of:
0.028917395 = score(doc=5704,freq=2.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.20052543 = fieldWeight in 5704, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=5704)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014)
0.19
0.19164318 = product of:
0.22997183 = sum of:
0.08315867 = weight(_text_:umfeld in 1338) [ClassicSimilarity], result of:
0.08315867 = score(doc=1338,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 1338, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=1338)
0.012892614 = weight(_text_:in in 1338) [ClassicSimilarity], result of:
0.012892614 = score(doc=1338,freq=14.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.19881277 = fieldWeight in 1338, product of:
3.7416575 = tf(freq=14.0), with freq of:
14.0 = termFreq=14.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=1338)
0.07616932 = weight(_text_:indexierung in 1338) [ClassicSimilarity], result of:
0.07616932 = score(doc=1338,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 1338, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=1338)
0.028237537 = weight(_text_:u in 1338) [ClassicSimilarity], result of:
0.028237537 = score(doc=1338,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 1338, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=1338)
0.029513694 = product of:
0.05902739 = sum of:
0.05902739 = weight(_text_:retrieval in 1338) [ClassicSimilarity], result of:
0.05902739 = score(doc=1338,freq=12.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.40932083 = fieldWeight in 1338, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=1338)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- A user's query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques model syntagmatic associations that infer two terms co-occur more often than by chance in natural language. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches to query expansion and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process improves retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008)
0.19
0.1885685 = product of:
0.22628221 = sum of:
0.08315867 = weight(_text_:umfeld in 2393) [ClassicSimilarity], result of:
0.08315867 = score(doc=2393,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 2393, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.014618848 = weight(_text_:in in 2393) [ClassicSimilarity], result of:
0.014618848 = score(doc=2393,freq=18.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.22543246 = fieldWeight in 2393, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.07616932 = weight(_text_:indexierung in 2393) [ClassicSimilarity], result of:
0.07616932 = score(doc=2393,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 2393, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.028237537 = weight(_text_:u in 2393) [ClassicSimilarity], result of:
0.028237537 = score(doc=2393,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 2393, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.02409783 = product of:
0.04819566 = sum of:
0.04819566 = weight(_text_:retrieval in 2393) [ClassicSimilarity], result of:
0.04819566 = score(doc=2393,freq=8.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.33420905 = fieldWeight in 2393, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Xu, B.; Lin, H.; Lin, Y.: Assessment of learning to rank methods for query expansion (2016)
0.19
0.18783665 = product of:
0.22540398 = sum of:
0.08315867 = weight(_text_:umfeld in 2929) [ClassicSimilarity], result of:
0.08315867 = score(doc=2929,freq=2.0), product of:
0.26788878 = queryWeight, product of:
5.619245 = idf(docFreq=435, maxDocs=44218)
0.047673445 = queryNorm
0.31042236 = fieldWeight in 2929, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.619245 = idf(docFreq=435, maxDocs=44218)
0.0390625 = fieldNorm(doc=2929)
0.010896247 = weight(_text_:in in 2929) [ClassicSimilarity], result of:
0.010896247 = score(doc=2929,freq=10.0), product of:
0.06484802 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.047673445 = queryNorm
0.16802745 = fieldWeight in 2929, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0390625 = fieldNorm(doc=2929)
0.07616932 = weight(_text_:indexierung in 2929) [ClassicSimilarity], result of:
0.07616932 = score(doc=2929,freq=2.0), product of:
0.25638393 = queryWeight, product of:
5.377919 = idf(docFreq=554, maxDocs=44218)
0.047673445 = queryNorm
0.29709086 = fieldWeight in 2929, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.377919 = idf(docFreq=554, maxDocs=44218)
0.0390625 = fieldNorm(doc=2929)
0.028237537 = weight(_text_:u in 2929) [ClassicSimilarity], result of:
0.028237537 = score(doc=2929,freq=2.0), product of:
0.15610404 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.047673445 = queryNorm
0.1808892 = fieldWeight in 2929, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=2929)
0.026942192 = product of:
0.053884383 = sum of:
0.053884383 = weight(_text_:retrieval in 2929) [ClassicSimilarity], result of:
0.053884383 = score(doc=2929,freq=10.0), product of:
0.14420812 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.047673445 = queryNorm
0.37365708 = fieldWeight in 2929, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2929)
0.5 = coord(1/2)
0.8333333 = coord(5/6)
- Abstract
- Pseudo relevance feedback, as an effective query expansion method, can significantly improve information retrieval performance. However, the method may negatively impact the retrieval performance when some irrelevant terms are used in the expanded query. Therefore, it is necessary to refine the expansion terms. Learning to rank methods have proven effective in information retrieval to solve ranking problems by ranking the most relevant documents at the top of the returned list, but few attempts have been made to employ learning to rank methods for term refinement in pseudo relevance feedback. This article proposes a novel framework to explore the feasibility of using learning to rank to optimize pseudo relevance feedback by means of reranking the candidate expansion terms. We investigate some learning approaches to choose the candidate terms and introduce some state-of-the-art learning to rank methods to refine the expansion terms. In addition, we propose two term labeling strategies and examine the usefulness of various term features to optimize the framework. Experimental results with three TREC collections show that our framework can effectively improve retrieval performance.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
