Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS
In the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords wh...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , , |
| التنسيق: | article |
| منشور في: |
2018
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/15974 https://doi.org/10.1016/j.datak.2018.07.007 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.sciencedirect.com/science/article/pii/S0169023X16301835 |
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| _version_ | 1864513471816663040 |
|---|---|
| author | Tekli, Joe |
| author2 | Chbeir, Richard Traina, Agma J.M. Traina Jr., Caetano Yetongnon, Kokou Ibanez, Carlos Raymundo Al Assad, Marc Kallas, Christian |
| author2_role | author author author author author author author |
| author_facet | Tekli, Joe Chbeir, Richard Traina, Agma J.M. Traina Jr., Caetano Yetongnon, Kokou Ibanez, Carlos Raymundo Al Assad, Marc Kallas, Christian |
| author_role | author |
| dc.creator.none.fl_str_mv | Tekli, Joe Chbeir, Richard Traina, Agma J.M. Traina Jr., Caetano Yetongnon, Kokou Ibanez, Carlos Raymundo Al Assad, Marc Kallas, Christian |
| dc.date.none.fl_str_mv | 2018 2018-10-13 2024-08-13T10:12:30Z 2024-08-13T10:12:30Z |
| dc.identifier.none.fl_str_mv | 0169-023X http://hdl.handle.net/10725/15974 https://doi.org/10.1016/j.datak.2018.07.007 Tekli, J., Chbeir, R., Traina, A. J., Traina Jr, C., Yetongnon, K., Ibañez, C. R., ... & Kallas, C. (2018). Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS. Data & Knowledge Engineering, 117, 133-173. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.sciencedirect.com/science/article/pii/S0169023X16301835 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Data & Knowledge Engineering |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords which are different from those used by the authors in indexing relevant documents, thus producing noisy and sometimes irrelevant results. In this paper, we address the problem of semantic-aware querying and provide a general framework for modeling and processing semantic-based keyword queries in textual databases, i.e., considering the lexical and semantic similarities/disparities when matching user query and data index terms. To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. To investigate the practicality and effectiveness of SemIndex, we discuss its physical design within a standard commercial RDBMS allowing to create, store, and query its graph structure, thus enabling the system to easily scale up and handle large volumes of data. We have conducted a battery of experiments to test the performance of SemIndex, evaluating its construction time, storage size, query processing time, and result quality, in comparison with legacy inverted index. Results highlight both the effectiveness and scalability of our approach. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_3ea751a0d1643b4f914a3a33c279c3cf |
| identifier_str_mv | 0169-023X Tekli, J., Chbeir, R., Traina, A. J., Traina Jr, C., Yetongnon, K., Ibañez, C. R., ... & Kallas, C. (2018). Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS. Data & Knowledge Engineering, 117, 133-173. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/15974 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMSTekli, JoeChbeir, RichardTraina, Agma J.M.Traina Jr., CaetanoYetongnon, KokouIbanez, Carlos RaymundoAl Assad, MarcKallas, ChristianIn the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords which are different from those used by the authors in indexing relevant documents, thus producing noisy and sometimes irrelevant results. In this paper, we address the problem of semantic-aware querying and provide a general framework for modeling and processing semantic-based keyword queries in textual databases, i.e., considering the lexical and semantic similarities/disparities when matching user query and data index terms. To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. To investigate the practicality and effectiveness of SemIndex, we discuss its physical design within a standard commercial RDBMS allowing to create, store, and query its graph structure, thus enabling the system to easily scale up and handle large volumes of data. We have conducted a battery of experiments to test the performance of SemIndex, evaluating its construction time, storage size, query processing time, and result quality, in comparison with legacy inverted index. Results highlight both the effectiveness and scalability of our approach.Published2024-08-13T10:12:30Z2024-08-13T10:12:30Z20182018-10-13Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0169-023Xhttp://hdl.handle.net/10725/15974https://doi.org/10.1016/j.datak.2018.07.007Tekli, J., Chbeir, R., Traina, A. J., Traina Jr, C., Yetongnon, K., Ibañez, C. R., ... & Kallas, C. (2018). Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS. Data & Knowledge Engineering, 117, 133-173.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://www.sciencedirect.com/science/article/pii/S0169023X16301835enData & Knowledge Engineeringinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/159742024-08-13T10:12:52Z |
| spellingShingle | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS Tekli, Joe |
| status_str | publishedVersion |
| title | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| title_full | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| title_fullStr | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| title_full_unstemmed | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| title_short | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| title_sort | Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS |
| url | http://hdl.handle.net/10725/15974 https://doi.org/10.1016/j.datak.2018.07.007 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.sciencedirect.com/science/article/pii/S0169023X16301835 |