Publication:
Similarity Search Techniques in Exploratory Search: A Review

dc.citedby3
dc.contributor.authorMahdi M.en_US
dc.contributor.authorAhmad A.R.en_US
dc.contributor.authorIsmail R.en_US
dc.contributor.authorid56727803900en_US
dc.contributor.authorid35589598800en_US
dc.contributor.authorid15839357700en_US
dc.date.accessioned2023-05-29T07:26:52Z
dc.date.available2023-05-29T07:26:52Z
dc.date.issued2019
dc.descriptionInformation retrieval; Content-based search; Document similarity; Exploratory search; Internet application; Multimedia database; Relevant documents; Similarity search; Unstructured data; Search enginesen_US
dc.description.abstractThe past decade has seen a dramatic increase in the amount of data captured and made available to users for research. This increase amplifies the difficulties users' face in finding the data most relevant to their information needs. The document similarity search is one of the most important topics in the field of information science, especially due to the popularity of the internet applications that deal with unstructured data sources such as World Wide Web. Efficiency of similarity search has become one of the most important issues. A typical example of similarity search is in multimedia databases that manage objects without structure, i.e. images, fingerprints or audio clips. Here similarity search is involved in retrieving the most similar fingerprint to a given one. Another example is in text retrieval which is present in many systems, from simple text editors (finding words similar to a given one to correct edition errors) to big search engines (retrieving relevant documents for a given query). This study explores the use of similarity search for text data in the form of a brief review using the interface provided as a service after content-based searches has been performed. The findings will give us ideas as to how to incorporate similarity searches within others search engine architecture. � 2018 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8650257
dc.identifier.doi10.1109/TENCON.2018.8650257
dc.identifier.epage2198
dc.identifier.scopus2-s2.0-85063197622
dc.identifier.spage2193
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85063197622&doi=10.1109%2fTENCON.2018.8650257&partnerID=40&md5=491183e634118f11d0739152278dbbf6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24772
dc.identifier.volume2018-October
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleIEEE Region 10 Annual International Conference, Proceedings/TENCON
dc.titleSimilarity Search Techniques in Exploratory Search: A Reviewen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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