期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2021
卷号：48
期号：1
语种：English
出版社：IAENG - International Association of Engineers
摘要：As the web grows, finding information from largedata repositories has become increasingly difficult not only dueto inadequate number of results that are relevant,but also dueto poor sorting of relevant results from those irrelevant. Thepresent search engines (SEs) use the query and response lookupprocess that does not provide precise results.Thus, researchershave gone beyond the paradigm to explore a new class of mcthodto seek information, which is called exploratory research that isopen-ended and its faceted search can improve the overallsearch process. Besides,many studies have begun tapping intoenhancement of web search results relevancy.The web reflectsvast heterogeneity, varying structure, and massive in volumes.Therefore,it is rather difficult to seek accurate outcomes asdesired. As such，visualisation and interactive graphics havebeen proposed as methods to manage massive amounts of resultsand to project essential features for the web pages.Additionally,searchengine controls reconstruction and reformulation ofqueries. As such,a search engine is prescnted in this study bydeveloping it on the cloud computing platform environment.The search engine is based on 'the idea of improving visualexploratory search (VExSearch) while exploring information inthe web. This particular notion reflects the process of seekingand combing through the vast information by using thecoordinated visualisation method，apart from minimising theeffort spent in seeking information per query.The VExSearchwas evaluated for its capability and performance and latercompared with IMDb^sEand CloudMiningSE.Thecomparafive results showed that the VExSearch was 66% moreaccurate than the other SEs. VExSearch also seemed to providethe most relevant results among all the three SEs,aside fromattaining an average improvement of 20% in terms of recall.
