-
Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005)
0.03
0.027645696 = product of:
0.082937084 = sum of:
0.0726894 = weight(_text_:ranking in 4708) [ClassicSimilarity], result of:
0.0726894 = score(doc=4708,freq=2.0), product of:
0.20271951 = queryWeight, product of:
5.4090285 = idf(docFreq=537, maxDocs=44218)
0.03747799 = queryNorm
0.35857132 = fieldWeight in 4708, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.4090285 = idf(docFreq=537, maxDocs=44218)
0.046875 = fieldNorm(doc=4708)
0.010247685 = product of:
0.030743055 = sum of:
0.030743055 = weight(_text_:29 in 4708) [ClassicSimilarity], result of:
0.030743055 = score(doc=4708,freq=2.0), product of:
0.13183585 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.03747799 = queryNorm
0.23319192 = fieldWeight in 4708, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.046875 = fieldNorm(doc=4708)
0.33333334 = coord(1/3)
0.33333334 = coord(2/6)
- Abstract
- Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontologybased KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.
- Source
- The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat
-
Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014)
0.03
0.026455574 = product of:
0.07936672 = sum of:
0.07344268 = weight(_text_:ranking in 1633) [ClassicSimilarity], result of:
0.07344268 = score(doc=1633,freq=6.0), product of:
0.20271951 = queryWeight, product of:
5.4090285 = idf(docFreq=537, maxDocs=44218)
0.03747799 = queryNorm
0.3622872 = fieldWeight in 1633, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
5.4090285 = idf(docFreq=537, maxDocs=44218)
0.02734375 = fieldNorm(doc=1633)
0.005924042 = product of:
0.017772125 = sum of:
0.017772125 = weight(_text_:22 in 1633) [ClassicSimilarity], result of:
0.017772125 = score(doc=1633,freq=2.0), product of:
0.13124153 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03747799 = queryNorm
0.1354154 = fieldWeight in 1633, 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=1633)
0.33333334 = coord(1/3)
0.33333334 = coord(2/6)
- Abstract
- Purpose - The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts. Design/methodology/approach - In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query. Findings - The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology "with and without query expansion" is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42. Practical implications - When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved. Originality/value - In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.
- Date
- 20. 1.2015 18:30:22
-
Baofu, P.: ¬The future of information architecture : conceiving a better way to understand taxonomy, network, and intelligence (2008)
0.02
0.0156014785 = product of:
0.09360887 = sum of:
0.09360887 = weight(_text_:suchmaschine in 2257) [ClassicSimilarity], result of:
0.09360887 = score(doc=2257,freq=4.0), product of:
0.21191008 = queryWeight, product of:
5.6542544 = idf(docFreq=420, maxDocs=44218)
0.03747799 = queryNorm
0.44173864 = fieldWeight in 2257, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
5.6542544 = idf(docFreq=420, maxDocs=44218)
0.0390625 = fieldNorm(doc=2257)
0.16666667 = coord(1/6)
- RSWK
- Suchmaschine / Information Retrieval
- Subject
- Suchmaschine / Information Retrieval
-
Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013)
0.00
0.0022772634 = product of:
0.013663581 = sum of:
0.013663581 = product of:
0.04099074 = sum of:
0.04099074 = weight(_text_:29 in 2245) [ClassicSimilarity], result of:
0.04099074 = score(doc=2245,freq=2.0), product of:
0.13183585 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.03747799 = queryNorm
0.31092256 = fieldWeight in 2245, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.0625 = fieldNorm(doc=2245)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Date
- 29. 9.2015 18:56:44
-
Atanassova, I.; Bertin, M.: Semantic facets for scientific information retrieval (2014)
0.00
0.0019926056 = product of:
0.011955633 = sum of:
0.011955633 = product of:
0.035866898 = sum of:
0.035866898 = weight(_text_:29 in 4471) [ClassicSimilarity], result of:
0.035866898 = score(doc=4471,freq=2.0), product of:
0.13183585 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.03747799 = queryNorm
0.27205724 = fieldWeight in 4471, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.0546875 = fieldNorm(doc=4471)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Source
- Semantic Web Evaluation Challenge. SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers. Eds.: V. Presutti et al
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
0.00
0.0019746807 = product of:
0.011848084 = sum of:
0.011848084 = product of:
0.03554425 = sum of:
0.03554425 = weight(_text_:22 in 1852) [ClassicSimilarity], result of:
0.03554425 = score(doc=1852,freq=2.0), product of:
0.13124153 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03747799 = queryNorm
0.2708308 = fieldWeight in 1852, 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=1852)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Date
- 11. 2.2011 18:22:58
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005)
0.00
0.0019746807 = product of:
0.011848084 = sum of:
0.011848084 = product of:
0.03554425 = sum of:
0.03554425 = weight(_text_:22 in 4324) [ClassicSimilarity], result of:
0.03554425 = score(doc=4324,freq=2.0), product of:
0.13124153 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03747799 = queryNorm
0.2708308 = fieldWeight in 4324, 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=4324)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Date
- 11. 2.2011 18:22:25
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
0.00
0.0016925833 = product of:
0.0101555 = sum of:
0.0101555 = product of:
0.030466499 = sum of:
0.030466499 = weight(_text_:22 in 2230) [ClassicSimilarity], result of:
0.030466499 = score(doc=2230,freq=2.0), product of:
0.13124153 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03747799 = queryNorm
0.23214069 = fieldWeight in 2230, 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=2230)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Source
- Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
-
Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008)
0.00
0.0014232898 = product of:
0.008539738 = sum of:
0.008539738 = product of:
0.025619213 = sum of:
0.025619213 = weight(_text_:29 in 2393) [ClassicSimilarity], result of:
0.025619213 = score(doc=2393,freq=2.0), product of:
0.13183585 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.03747799 = queryNorm
0.19432661 = fieldWeight in 2393, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.0390625 = fieldNorm(doc=2393)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Date
- 9.11.2008 13:07:29
-
Hannech, A.: Système de recherche d'information étendue basé sur une projection multi-espaces (2018)
0.00
5.6931586E-4 = product of:
0.0034158952 = sum of:
0.0034158952 = product of:
0.010247685 = sum of:
0.010247685 = weight(_text_:29 in 4472) [ClassicSimilarity], result of:
0.010247685 = score(doc=4472,freq=2.0), product of:
0.13183585 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.03747799 = queryNorm
0.07773064 = fieldWeight in 4472, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.015625 = fieldNorm(doc=4472)
0.33333334 = coord(1/3)
0.16666667 = coord(1/6)
- Date
- 29. 9.2018 18:57:38
