User interest driven semantic query expansion for effective web search
Retrieving user-relevant content from a large volume of data available on the Web via an input query is a difficult task. A user query may not be able to specify user information needs due to the ambiguous and limited number of query terms. The semantic query expansion (QE) strategy offers a solutio...
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| Format: | Article |
| Language: | English |
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Al-Zaytoonah University of Jordan
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/31759/ http://umpir.ump.edu.my/id/eprint/31759/1/User%20Interest%20Driven%20Semantic%20Query.pdf |
| _version_ | 1848823849664118784 |
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| author | Raza, Muhammad Ahsan Rahmah, Mokhtar Qaswar, Fahad Shafqat, Anam Rauf, Muhammad Raza, Sehrish |
| author_facet | Raza, Muhammad Ahsan Rahmah, Mokhtar Qaswar, Fahad Shafqat, Anam Rauf, Muhammad Raza, Sehrish |
| author_sort | Raza, Muhammad Ahsan |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Retrieving user-relevant content from a large volume of data available on the Web via an input query is a difficult task. A user query may not be able to specify user information needs due to the ambiguous and limited number of query terms. The semantic query expansion (QE) strategy offers a solution to this problem by expanding the query with additional terms, which are semantically similar to the original query. However, this strategy does not consider individual user interest in the generation of expansion terms. In this article, semantic QE is improved by combining the notion of ontology knowledge and user interest. The proposed semantic QE technique involves a computing domain of the input query via ontology, generates expansion terms from the user browsing history, and finally selects expansion terms that represent user preferences on the basis of the semantic similarity between expansion terms and query and user feedback. The experimental evaluation indicates that expanded queries produced by the proposed technique retrieve more personalized contents over Web search than initial user queries. The obtained results achieve 86.4% average precision, which proves a positive impact of incorporating user preferences in semantic QE. |
| first_indexed | 2025-11-15T03:03:40Z |
| format | Article |
| id | ump-31759 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:03:40Z |
| publishDate | 2021 |
| publisher | Al-Zaytoonah University of Jordan |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-317592021-09-14T14:30:59Z http://umpir.ump.edu.my/id/eprint/31759/ User interest driven semantic query expansion for effective web search Raza, Muhammad Ahsan Rahmah, Mokhtar Qaswar, Fahad Shafqat, Anam Rauf, Muhammad Raza, Sehrish QA75 Electronic computers. Computer science Retrieving user-relevant content from a large volume of data available on the Web via an input query is a difficult task. A user query may not be able to specify user information needs due to the ambiguous and limited number of query terms. The semantic query expansion (QE) strategy offers a solution to this problem by expanding the query with additional terms, which are semantically similar to the original query. However, this strategy does not consider individual user interest in the generation of expansion terms. In this article, semantic QE is improved by combining the notion of ontology knowledge and user interest. The proposed semantic QE technique involves a computing domain of the input query via ontology, generates expansion terms from the user browsing history, and finally selects expansion terms that represent user preferences on the basis of the semantic similarity between expansion terms and query and user feedback. The experimental evaluation indicates that expanded queries produced by the proposed technique retrieve more personalized contents over Web search than initial user queries. The obtained results achieve 86.4% average precision, which proves a positive impact of incorporating user preferences in semantic QE. Al-Zaytoonah University of Jordan 2021-07 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/31759/1/User%20Interest%20Driven%20Semantic%20Query.pdf Raza, Muhammad Ahsan and Rahmah, Mokhtar and Qaswar, Fahad and Shafqat, Anam and Rauf, Muhammad and Raza, Sehrish (2021) User interest driven semantic query expansion for effective web search. International Journal of Advances in Soft Computing and its Applications, 13 (2). pp. 11-24. ISSN 2074-8523. (Published) http://ijasca.zuj.edu.jo/PapersUploaded/2021.2.2.pdf |
| spellingShingle | QA75 Electronic computers. Computer science Raza, Muhammad Ahsan Rahmah, Mokhtar Qaswar, Fahad Shafqat, Anam Rauf, Muhammad Raza, Sehrish User interest driven semantic query expansion for effective web search |
| title | User interest driven semantic query expansion for effective web search |
| title_full | User interest driven semantic query expansion for effective web search |
| title_fullStr | User interest driven semantic query expansion for effective web search |
| title_full_unstemmed | User interest driven semantic query expansion for effective web search |
| title_short | User interest driven semantic query expansion for effective web search |
| title_sort | user interest driven semantic query expansion for effective web search |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/31759/ http://umpir.ump.edu.my/id/eprint/31759/ http://umpir.ump.edu.my/id/eprint/31759/1/User%20Interest%20Driven%20Semantic%20Query.pdf |