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Context identification of scientific papers via agent-based model for text mining (ABM-TM)

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dc.citedby4
dc.contributor.authorMahmoud M.A.en_US
dc.contributor.authorAhmad M.S.en_US
dc.contributor.authorYusoff M.Z.M.en_US
dc.contributor.authorMustapha A.en_US
dc.contributor.authorid55247787300en_US
dc.contributor.authorid56036880900en_US
dc.contributor.authorid22636590200en_US
dc.contributor.authorid57200530694en_US
dc.date.accessioned2023-05-29T06:02:12Z
dc.date.available2023-05-29T06:02:12Z
dc.date.issued2015
dc.description.abstractIn this paper, we propose an agent-based text mining algorithm to extract potential context of papers published in the WWW. A user provides the agent with keywords and assigns a threshold value for each given keyword, the agent in turn attempts to find papers that match the keywords within a defined threshold. To achieve context recognition, the algorithm mines the keywords and identifies the potential context from analysing a paper�s abstract. The mining process entails data cleaning, formatting, filtering, and identifying the candidate keywords. Subsequently, based on the strength of each keyword and the threshold value, the algorithm facilitates the identification of the paper�s potential context. � Springer International Publishing Switzerland 2015.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-319-10774-5_5
dc.identifier.epage61
dc.identifier.scopus2-s2.0-84921526597
dc.identifier.spage51
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84921526597&doi=10.1007%2f978-3-319-10774-5_5&partnerID=40&md5=3a4b0e97f1d84b4835d35b1e45bebdd0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22576
dc.identifier.volume572
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleStudies in Computational Intelligence
dc.titleContext identification of scientific papers via agent-based model for text mining (ABM-TM)en_US
dc.typeArticleen_US
dspace.entity.typePublication
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