Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012)
0.01
0.0052332124 = product of:
0.036632486 = sum of:
0.036632486 = product of:
0.09158121 = sum of:
0.0439427 = weight(_text_:retrieval in 3829) [ClassicSimilarity], result of:
0.0439427 = score(doc=3829,freq=8.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = 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)
0.047638513 = weight(_text_:system in 3829) [ClassicSimilarity], result of:
0.047638513 = score(doc=3829,freq=8.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.41757566 = fieldWeight in 3829, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.046875 = fieldNorm(doc=3829)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- 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.
