HyKSS: Hybrid Keyword and Semantic Search
| Autor: | Del T. Scott, Andrew Zitzelberger, David W. Embley, Stephen W. Liddle |
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| Rok vydání: | 2014 |
| Předmět: |
Information retrieval
Concept search Computer Networks and Communications Computer science business.industry media_common.quotation_subject Semantic search computer.file_format Ambiguity Ranking (information retrieval) Annotation Artificial Intelligence SPARQL Quality (business) Isolation (database systems) business computer Information Systems media_common |
| Zdroj: | Journal on Data Semantics. 4:213-229 |
| ISSN: | 1861-2040 1861-2032 |
| DOI: | 10.1007/s13740-014-0046-4 |
| Popis: | Keyword search suffers from a number of issues: ambiguity, synonymy, and an inability to handle semantic constraints. Semantic search helps resolve these issues but is limited by the quality of annotations which are likely to be incomplete or imprecise. Hybrid search, a search technique that combines the merits of both keyword and semantic search, appears to be a promising solution. In this paper we describe and evaluate HyKSS, a hybrid search system driven by extraction ontologies for both annotation creation and query interpretation. For displaying results, HyKSS uses a dynamic ranking algorithm. We show that over data sets of short topical documents, the HyKSS ranking algorithm outperforms both keyword and semantic search in isolation, as well as a number of other non-HyKSS hybrid approaches to ranking. |
| Databáze: | OpenAIRE |
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