Ontology mining for semantic interpretation of user information needs
Paper
Paper/Presentation Title | Ontology mining for semantic interpretation of user information needs |
---|---|
Presentation Type | Paper |
Authors | Tao, Xiaohui (Author), Li, Yuefeng (Author) and Nayak, Richi (Author) |
Editors | Zhang, Zili and Siekmann, Jorg |
Journal or Proceedings Title | Lecture Notes in Computer Science (Book series) |
Journal Citation | 4798, pp. 313-324 |
Number of Pages | 12 |
Year | 2007 |
Publisher | Springer |
Place of Publication | Germany |
ISSN | 1611-3349 |
0302-9743 | |
ISBN | 9783540767183 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-540-76719-0_32 |
Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/978-3-540-76719-0_32 |
Conference/Event | 2nd International Conference on Knowledge Science, Engineering, and Management (KSEM 2007) |
Event Details | Rank B B B B B B B B B |
Event Details | 2nd International Conference on Knowledge Science, Engineering, and Management (KSEM 2007) Event Date 28 to end of 30 Nov 2007 Event Location Melbourne, Australia |
Abstract | Ontology is an important technique for semantic interpre- tation. However, the most existing ontologies are simple computational models based on only 'super-' and 'sub-class' relationships. In this paper, a computational model is presented for ontology mining, which analyzes the semantic relations of 'part-of', 'kind-of' and 'related-to', and interprets the semantics of individual information need. The model is evaluated by comparing the knowledge mined by it, against the knowledge generated manually by linguists. The proposed model enhances Web information gathering from keyword-based to subject(concept)-based. It is a new contribution to knowledge engineering and management. |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
460508. Information retrieval and web search | |
470409. Linguistic structures (incl. phonology, morphology and syntax) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Queensland University of Technology |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q101z/ontology-mining-for-semantic-interpretation-of-user-information-needs
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