Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012)
0.01
0.01478128 = product of:
0.06897931 = sum of:
0.020922182 = weight(_text_:web in 3829) [ClassicSimilarity], result of:
0.020922182 = score(doc=3829,freq=2.0), product of:
0.09670874 = queryWeight, product of:
3.2635105 = idf(docFreq=4597, maxDocs=44218)
0.029633347 = queryNorm
0.21634221 = fieldWeight in 3829, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2635105 = idf(docFreq=4597, maxDocs=44218)
0.046875 = fieldNorm(doc=3829)
0.012107591 = weight(_text_:information in 3829) [ClassicSimilarity], result of:
0.012107591 = score(doc=3829,freq=8.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.23274569 = fieldWeight in 3829, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=3829)
0.03594954 = weight(_text_:retrieval in 3829) [ClassicSimilarity], result of:
0.03594954 = score(doc=3829,freq=8.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.40105087 = fieldWeight in 3829, 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=3829)
0.21428572 = coord(3/14)
- Abstract
- In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.
- Source
- Information Systems. 37(2012) no. 4, S.294-305
- Theme
- Semantic Web