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VExSearch: Improving Visualizations Results for Web-based Information Exploration and Refinement

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dc.contributor.authorMahdi M.N.en_US
dc.contributor.authorAhmad A.R.en_US
dc.contributor.authorIsmail R.en_US
dc.contributor.authorBuhari A.M.en_US
dc.contributor.authorid56727803900en_US
dc.contributor.authorid35589598800en_US
dc.contributor.authorid15839357700en_US
dc.contributor.authorid56525158000en_US
dc.date.accessioned2023-05-29T09:11:53Z
dc.date.available2023-05-29T09:11:53Z
dc.date.issued2021
dc.descriptionVisualization; Websites; Class of methods; Cloud computing platforms; Essential features; Exploratory research; Exploratory search; Interactive graphics; Web search results; Web-based information; Search enginesen_US
dc.description.abstractAs the web grows, finding information from large data repositories has become increasingly difficult not only due to inadequate number of results that are relevant, but also due to poor sorting of relevant results from those irrelevant. The present search engines (SEs) use the query and response lookup process that does not provide precise results. Thus, researchers have gone beyond the paradigm to explore a new class of method to seek information, which is called exploratory research that is open-ended and its faceted search can improve the overall search process. Besides, many studies have begun tapping into enhancement of web search results relevancy. The web reflects vast heterogeneity, varying structure, and massive in volumes. Therefore, it is rather difficult to seek accurate outcomes as desired. As such, visualisation and interactive graphics have been proposed as methods to manage massive amounts of results and to project essential features for the web pages. Additionally, search engine controls reconstruction and reformulation of queries. As such, a search engine is presented in this study by developing it on the cloud computing platform environment The search engine is based on the idea of improving visual exploratory search (VExSearch) while exploring information in the web. This particular notion reflects the process of seeking and combing through the vast information by using the coordinated visualisation method, apart from minimising the effort spent in seeking information per query. The VExSearch was evaluated for its capability and performance and later compared with IMDb SE and CloudMining SE. The comparative results showed that the VExSearch was 66% more accurate than the other SEs. VExSearch also seemed to provide the most relevant results among all the three SEs, aside from attaining an average improvement of 20% in terms of recall. � 2021, IAENG International Journal of Computer Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.epage15
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85104091493
dc.identifier.spage1
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85104091493&partnerID=40&md5=afa270af824e883ac6db7b8aa4d46f02
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26553
dc.identifier.volume48
dc.publisherInternational Association of Engineersen_US
dc.sourceScopus
dc.sourcetitleIAENG International Journal of Computer Science
dc.titleVExSearch: Improving Visualizations Results for Web-based Information Exploration and Refinementen_US
dc.typeArticleen_US
dspace.entity.typePublication
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