-
Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000)
0.10
0.09637429 = product of:
0.12849905 = sum of:
0.03442384 = weight(_text_:c in 105) [ClassicSimilarity], result of:
0.03442384 = score(doc=105,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.22866541 = fieldWeight in 105, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.046875 = fieldNorm(doc=105)
0.06369243 = weight(_text_:et in 105) [ClassicSimilarity], result of:
0.06369243 = score(doc=105,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.3110389 = fieldWeight in 105, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.046875 = fieldNorm(doc=105)
0.03038278 = product of:
0.06076556 = sum of:
0.06076556 = weight(_text_:al in 105) [ClassicSimilarity], result of:
0.06076556 = score(doc=105,freq=2.0), product of:
0.20001286 = queryWeight, product of:
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.043643 = queryNorm
0.30380827 = fieldWeight in 105, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.046875 = fieldNorm(doc=105)
0.5 = coord(1/2)
0.75 = coord(3/4)
- Source
- Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
-
Ruthven, I.; Lalmas, M.: Selective relevance feedback using term characteristics (1999)
0.08
0.07839601 = product of:
0.15679201 = sum of:
0.106154054 = weight(_text_:et in 3824) [ClassicSimilarity], result of:
0.106154054 = score(doc=3824,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.5183982 = fieldWeight in 3824, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.078125 = fieldNorm(doc=3824)
0.050637968 = product of:
0.101275936 = sum of:
0.101275936 = weight(_text_:al in 3824) [ClassicSimilarity], result of:
0.101275936 = score(doc=3824,freq=2.0), product of:
0.20001286 = queryWeight, product of:
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.043643 = queryNorm
0.5063471 = fieldWeight in 3824, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.078125 = fieldNorm(doc=3824)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Source
- Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al
-
Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004)
0.06
0.061684094 = product of:
0.12336819 = sum of:
0.052543577 = weight(_text_:et in 2509) [ClassicSimilarity], result of:
0.052543577 = score(doc=2509,freq=4.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.25659403 = fieldWeight in 2509, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.02734375 = fieldNorm(doc=2509)
0.070824616 = sum of:
0.05012903 = weight(_text_:al in 2509) [ClassicSimilarity], result of:
0.05012903 = score(doc=2509,freq=4.0), product of:
0.20001286 = queryWeight, product of:
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.043643 = queryNorm
0.25062904 = fieldWeight in 2509, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.02734375 = fieldNorm(doc=2509)
0.020695586 = weight(_text_:22 in 2509) [ClassicSimilarity], result of:
0.020695586 = score(doc=2509,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = queryNorm
0.1354154 = fieldWeight in 2509, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02734375 = fieldNorm(doc=2509)
0.5 = coord(2/4)
- Content
- "Most Web search engines accept natural language queries, perform some kind of fuzzy matching and produce ranked output, displaying first the documents that are most likely to be relevant. On the other hand, most library online public access catalogs (OPACs) an the Web are still Boolean retrieval systems that perform exact matching, and require users to express their search requests precisely in a Boolean search language and to refine their search statements to improve the search results. It is well-documented that users have difficulty searching Boolean OPACs effectively (e.g. Borgman, 1996; Ensor, 1992; Wallace, 1993). One approach to making OPACs easier to use is to develop a natural language search interface that acts as a middleware between the user's Web browser and the OPAC system. The search interface can accept a natural language query from the user and reformulate it as a series of Boolean search statements that are then submitted to the OPAC. The records retrieved by the OPAC are ranked by the search interface before forwarding them to the user's Web browser. The user, then, does not need to interact directly with the Boolean OPAC but with the natural language search interface or search intermediary. The search interface interacts with the OPAC system an the user's behalf. The advantage of this approach is that no modification to the OPAC or library system is required. Furthermore, the search interface can access multiple OPACs, acting as a meta search engine, and integrate search results from various OPACs before sending them to the user. The search interface needs to incorporate a method for converting the user's natural language query into a series of Boolean search statements, and for ranking the OPAC records retrieved. The purpose of this study was to develop a relevancyranking algorithm for a search interface to Boolean OPAC systems. This is part of an on-going effort to develop a knowledge-based search interface to OPACs called the E-Referencer (Khoo et al., 1998, 1999; Poo et al., 2000). E-Referencer v. 2 that has been implemented applies a repertoire of initial search strategies and reformulation strategies to retrieve records from OPACs using the Z39.50 protocol, and also assists users in mapping query keywords to the Library of Congress subject headings."
- Source
- Electronic library. 22(2004) no.2, S.112-120
-
Bodoff, D.; Robertson, S.: ¬A new unified probabilistic model (2004)
0.05
0.047037605 = product of:
0.09407521 = sum of:
0.06369243 = weight(_text_:et in 2129) [ClassicSimilarity], result of:
0.06369243 = score(doc=2129,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.3110389 = fieldWeight in 2129, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.046875 = fieldNorm(doc=2129)
0.03038278 = product of:
0.06076556 = sum of:
0.06076556 = weight(_text_:al in 2129) [ClassicSimilarity], result of:
0.06076556 = score(doc=2129,freq=2.0), product of:
0.20001286 = queryWeight, product of:
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.043643 = queryNorm
0.30380827 = fieldWeight in 2129, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.046875 = fieldNorm(doc=2129)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Abstract
- This paper proposes a new unified probabilistic model. Two previous models, Robertson et al.'s "Model 0" and "Model 3," each have strengths and weaknesses. The strength of Model 0 not found in Model 3, is that it does not require relevance data about the particular document or query, and, related to that, its probability estimates are straightforward. The strength of Model 3 not found in Model 0 is that it can utilize feedback information about the particular document and query in question. In this paper we introduce a new unified probabilistic model that combines these strengths: the expression of its probabilities is straightforward, it does not require that data must be available for the particular document or query in question, but it can utilize such specific data if it is available. The model is one way to resolve the difficulty of combining two marginal views in probabilistic retrieval.
-
Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998)
0.05
0.045128368 = product of:
0.090256736 = sum of:
0.069561146 = weight(_text_:c in 1319) [ClassicSimilarity], result of:
0.069561146 = score(doc=1319,freq=6.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.46207014 = fieldWeight in 1319, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.0546875 = fieldNorm(doc=1319)
0.020695586 = product of:
0.04139117 = sum of:
0.04139117 = weight(_text_:22 in 1319) [ClassicSimilarity], result of:
0.04139117 = score(doc=1319,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = 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)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Date
- 1. 8.1996 22:08:06
-
Agosti, M.; Pretto, L.: ¬A theoretical study of a generalized version of kleinberg's HITS algorithm (2005)
0.04
0.039198004 = product of:
0.07839601 = sum of:
0.053077027 = weight(_text_:et in 4) [ClassicSimilarity], result of:
0.053077027 = score(doc=4,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.2591991 = fieldWeight in 4, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.0390625 = fieldNorm(doc=4)
0.025318984 = product of:
0.050637968 = sum of:
0.050637968 = weight(_text_:al in 4) [ClassicSimilarity], result of:
0.050637968 = score(doc=4,freq=2.0), product of:
0.20001286 = queryWeight, product of:
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.043643 = queryNorm
0.25317356 = fieldWeight in 4, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.582931 = idf(docFreq=1228, maxDocs=44218)
0.0390625 = fieldNorm(doc=4)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Abstract
- Kleinberg's HITS (Hyperlink-Induced Topic Search) algorithm (Kleinberg 1999), which was originally developed in a Web context, tries to infer the authoritativeness of a Web page in relation to a specific query using the structure of a subgraph of the Web graph, which is obtained considering this specific query. Recent applications of this algorithm in contexts far removed from that of Web searching (Bacchin, Ferro and Melucci 2002, Ng et al. 2001) inspired us to study the algorithm in the abstract, independently of its particular applications, trying to mathematically illuminate its behaviour. In the present paper we detail this theoretical analysis. The original work starts from the definition of a revised and more general version of the algorithm, which includes the classic one as a particular case. We perform an analysis of the structure of two particular matrices, essential to studying the behaviour of the algorithm, and we prove the convergence of the algorithm in the most general case, finding the analytic expression of the vectors to which it converges. Then we study the symmetry of the algorithm and prove the equivalence between the existence of symmetry and the independence from the order of execution of some basic operations on initial vectors. Finally, we expound some interesting consequences of our theoretical results.
-
Courtois, M.P.; Berry, M.W.: Results ranking in Web search engines (1999)
0.04
0.037531126 = product of:
0.1501245 = sum of:
0.1501245 = weight(_text_:et in 3726) [ClassicSimilarity], result of:
0.1501245 = score(doc=3726,freq=4.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.7331258 = fieldWeight in 3726, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.078125 = fieldNorm(doc=3726)
0.25 = coord(1/4)
- Abstract
- Comparaison des méthodes de classement de 5 moteurs de recherche (AltaVista, HotBot, Excie, Infoseek et Lycos). Sont testées la présence de tous les mots, la proximité et la localisation
-
Faloutsos, C.: Signature files (1992)
0.03
0.034775272 = product of:
0.069550544 = sum of:
0.04589845 = weight(_text_:c in 3499) [ClassicSimilarity], result of:
0.04589845 = score(doc=3499,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.3048872 = fieldWeight in 3499, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.0625 = fieldNorm(doc=3499)
0.023652097 = product of:
0.047304194 = sum of:
0.047304194 = weight(_text_:22 in 3499) [ClassicSimilarity], result of:
0.047304194 = score(doc=3499,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = queryNorm
0.30952093 = fieldWeight in 3499, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=3499)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Date
- 7. 5.1999 15:22:48
-
Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006)
0.03
0.027675724 = product of:
0.055351447 = sum of:
0.040568884 = weight(_text_:c in 56) [ClassicSimilarity], result of:
0.040568884 = score(doc=56,freq=4.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.2694848 = fieldWeight in 56, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.0390625 = fieldNorm(doc=56)
0.014782562 = product of:
0.029565124 = sum of:
0.029565124 = weight(_text_:22 in 56) [ClassicSimilarity], result of:
0.029565124 = score(doc=56,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = 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)
0.5 = coord(1/2)
0.5 = coord(2/4)
- 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
-
Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
0.03
0.026081456 = product of:
0.05216291 = sum of:
0.03442384 = weight(_text_:c in 2419) [ClassicSimilarity], result of:
0.03442384 = score(doc=2419,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.22866541 = fieldWeight in 2419, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.046875 = fieldNorm(doc=2419)
0.017739072 = product of:
0.035478145 = sum of:
0.035478145 = weight(_text_:22 in 2419) [ClassicSimilarity], result of:
0.035478145 = score(doc=2419,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = 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)
0.5 = coord(1/2)
0.5 = coord(2/4)
- Date
- 16.11.2008 16:22:48
-
Salton, G.; Buckley, C.: Parallel text search methods (1988)
0.02
0.022949224 = product of:
0.0917969 = sum of:
0.0917969 = weight(_text_:c in 404) [ClassicSimilarity], result of:
0.0917969 = score(doc=404,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.6097744 = fieldWeight in 404, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.125 = fieldNorm(doc=404)
0.25 = coord(1/4)
-
Daniowicz, C.; Baliski, J.: Document ranking based upon Markov chains (2001)
0.02
0.02008057 = product of:
0.08032228 = sum of:
0.08032228 = weight(_text_:c in 5388) [ClassicSimilarity], result of:
0.08032228 = score(doc=5388,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.5335526 = fieldWeight in 5388, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.109375 = fieldNorm(doc=5388)
0.25 = coord(1/4)
-
Belkin, N.J.; Cool, C.; Koenemann, J.; Ng, K.B.; Park, S.: Using relevance feedback and ranking in interactive searching (1996)
0.02
0.01721192 = product of:
0.06884768 = sum of:
0.06884768 = weight(_text_:c in 7588) [ClassicSimilarity], result of:
0.06884768 = score(doc=7588,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.45733082 = fieldWeight in 7588, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.09375 = fieldNorm(doc=7588)
0.25 = coord(1/4)
-
Salton, G.; Buckley, C.: Term-weighting approaches in automatic text retrieval (1988)
0.02
0.01721192 = product of:
0.06884768 = sum of:
0.06884768 = weight(_text_:c in 1938) [ClassicSimilarity], result of:
0.06884768 = score(doc=1938,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.45733082 = fieldWeight in 1938, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.09375 = fieldNorm(doc=1938)
0.25 = coord(1/4)
-
Cole, C.: Intelligent information retrieval: diagnosing information need : Part I: the theoretical framework for developing an intelligent IR tool (1998)
0.02
0.01721192 = product of:
0.06884768 = sum of:
0.06884768 = weight(_text_:c in 6431) [ClassicSimilarity], result of:
0.06884768 = score(doc=6431,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.45733082 = fieldWeight in 6431, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.09375 = fieldNorm(doc=6431)
0.25 = coord(1/4)
-
Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998)
0.02
0.01721192 = product of:
0.06884768 = sum of:
0.06884768 = weight(_text_:c in 6432) [ClassicSimilarity], result of:
0.06884768 = score(doc=6432,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.45733082 = fieldWeight in 6432, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.09375 = fieldNorm(doc=6432)
0.25 = coord(1/4)
-
Bauckhage, C.: Marginalizing over the PageRank damping factor (2014)
0.01
0.014343265 = product of:
0.05737306 = sum of:
0.05737306 = weight(_text_:c in 928) [ClassicSimilarity], result of:
0.05737306 = score(doc=928,freq=2.0), product of:
0.1505424 = queryWeight, product of:
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.043643 = queryNorm
0.381109 = fieldWeight in 928, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.4494052 = idf(docFreq=3817, maxDocs=44218)
0.078125 = fieldNorm(doc=928)
0.25 = coord(1/4)
-
Widyantoro, D.H.; Ioerger, T.R.; Yen, J.: Learning user Interest dynamics with a three-descriptor representation (2001)
0.01
0.013269257 = product of:
0.053077027 = sum of:
0.053077027 = weight(_text_:et in 5185) [ClassicSimilarity], result of:
0.053077027 = score(doc=5185,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.2591991 = fieldWeight in 5185, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.0390625 = fieldNorm(doc=5185)
0.25 = coord(1/4)
- Abstract
- The use of documents ranked high by user feedback to profile user interests is commonly done with Rocchio's `s algorithm which uses a single list of attribute value pairs called a descriptor to carry term value weights for an individual. Negative feed back on old preferences or positive feedback on new preferences adjusts the descriptor at a fixed, predetermined, and often slow pace. Widyantoro, et alia, suggest a three descriptor model which adds two short term interest descriptors, one each for positive and negative feedback. User short term interest in a particular document is computed by subtracting the similarity measure with the negative descriptor from the similarity measure with the positive descriptor. Using a constant to represent the desired impact of long and short term interests these values may be summed for a single interest value. Using the Reuters 21578 1.0 test collection split into training and test sets, topics with at least 100 documents in a tight cluster were chosen. The TDR handles change well showing better recovery speed and accuracy than the single descriptor model. The nearest neighbor update strategy appears to keep the category concept relatively consistent when multiple TDRs are used.
-
Chen, Z.; Meng, X.; Fowler, R.H.; Zhu, B.: Real-time adaptive feature and document learning for Web search (2001)
0.01
0.013269257 = product of:
0.053077027 = sum of:
0.053077027 = weight(_text_:et in 5209) [ClassicSimilarity], result of:
0.053077027 = score(doc=5209,freq=2.0), product of:
0.20477319 = queryWeight, product of:
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.043643 = queryNorm
0.2591991 = fieldWeight in 5209, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.692005 = idf(docFreq=1101, maxDocs=44218)
0.0390625 = fieldNorm(doc=5209)
0.25 = coord(1/4)
- Abstract
- Chen et alia report on the design of FEATURES, a web search engine with adaptive features based on minimal relevance feedback. Rather than developing user profiles from previous searcher activity either at the server or client location, or updating indexes after search completion, FEATURES allows for index and user characterization files to be updated during query modification on retrieval from a general purpose search engine. Indexing terms relevant to a query are defined as the union of all terms assigned to documents retrieved by the initial search run and are used to build a vector space model on this retrieved set. The top ten weighted terms are presented to the user for a relevant non-relevant choice which is used to modify the term weights. Documents are chosen if their summed term weights are greater than some threshold. A user evaluation of the top ten ranked documents as non-relevant will decrease these term weights and a positive judgement will increase them. A new ordering of the retrieved set will generate new display lists of terms and documents. Precision is improved in a test on Alta Vista searches.
-
Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986)
0.01
0.011826049 = product of:
0.047304194 = sum of:
0.047304194 = product of:
0.09460839 = sum of:
0.09460839 = weight(_text_:22 in 402) [ClassicSimilarity], result of:
0.09460839 = score(doc=402,freq=2.0), product of:
0.15283036 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043643 = queryNorm
0.61904186 = fieldWeight in 402, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.125 = fieldNorm(doc=402)
0.5 = coord(1/2)
0.25 = coord(1/4)
- Source
- Information processing and management. 22(1986) no.6, S.465-476
