Effective semantic search using thematic similarity
Most existing semantic search systems expand search keywords using domain ontology to deal with semantic heterogeneity. They focus on matching the semantic similarity of individual keywords in a multiple-keywords query; however, they ignore the semantic relationships that exist among the keywords of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2014-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157813000359 |
| _version_ | 1818012688729505792 |
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| author | Sharifullah Khan Jibran Mustafa |
| author_facet | Sharifullah Khan Jibran Mustafa |
| author_sort | Sharifullah Khan |
| collection | DOAJ |
| description | Most existing semantic search systems expand search keywords using domain ontology to deal with semantic heterogeneity. They focus on matching the semantic similarity of individual keywords in a multiple-keywords query; however, they ignore the semantic relationships that exist among the keywords of the query themselves. The systems return less relevant answers for these types of queries. More relevant documents for a multiple-keywords query can be retrieved if the systems know the relationships that exist among multiple keywords in the query. The proposed search methodology matches patterns of keywords for capturing the context of keywords, and then the relevant documents are ranked according to their pattern relevance score. A prototype system has been implemented to validate the proposed search methodology. The system has been compared with existing systems for evaluation. The results demonstrate improvement in precision and recall of search. |
| first_indexed | 2024-04-14T06:23:30Z |
| format | Article |
| id | doaj.art-6acb7b1553c9419fb63d033f4237b7d2 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-14T06:23:30Z |
| publishDate | 2014-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-6acb7b1553c9419fb63d033f4237b7d22022-12-22T02:07:56ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782014-07-0126216116910.1016/j.jksuci.2013.10.006Effective semantic search using thematic similaritySharifullah KhanJibran MustafaMost existing semantic search systems expand search keywords using domain ontology to deal with semantic heterogeneity. They focus on matching the semantic similarity of individual keywords in a multiple-keywords query; however, they ignore the semantic relationships that exist among the keywords of the query themselves. The systems return less relevant answers for these types of queries. More relevant documents for a multiple-keywords query can be retrieved if the systems know the relationships that exist among multiple keywords in the query. The proposed search methodology matches patterns of keywords for capturing the context of keywords, and then the relevant documents are ranked according to their pattern relevance score. A prototype system has been implemented to validate the proposed search methodology. The system has been compared with existing systems for evaluation. The results demonstrate improvement in precision and recall of search.http://www.sciencedirect.com/science/article/pii/S1319157813000359Semantic searchThematic similaritySemantic heterogeneityRDF triplesInformation retrieval |
| spellingShingle | Sharifullah Khan Jibran Mustafa Effective semantic search using thematic similarity Journal of King Saud University: Computer and Information Sciences Semantic search Thematic similarity Semantic heterogeneity RDF triples Information retrieval |
| title | Effective semantic search using thematic similarity |
| title_full | Effective semantic search using thematic similarity |
| title_fullStr | Effective semantic search using thematic similarity |
| title_full_unstemmed | Effective semantic search using thematic similarity |
| title_short | Effective semantic search using thematic similarity |
| title_sort | effective semantic search using thematic similarity |
| topic | Semantic search Thematic similarity Semantic heterogeneity RDF triples Information retrieval |
| url | http://www.sciencedirect.com/science/article/pii/S1319157813000359 |
| work_keys_str_mv | AT sharifullahkhan effectivesemanticsearchusingthematicsimilarity AT jibranmustafa effectivesemanticsearchusingthematicsimilarity |