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Recommending related articles in wikipedia via a topic-based model

dc.contributor.authorSriurai, Wongkot
dc.contributor.authorMeesad, Phayung
dc.contributor.authorHaruechaiyasak, Choochart
dc.contributor.editorErfurth, Christian
dc.contributor.editorEichler, Gerald
dc.contributor.editorSchau, Volkmar
dc.date.accessioned2019-02-20T10:21:04Z
dc.date.available2019-02-20T10:21:04Z
dc.date.issued2009
dc.description.abstractWikipedia is currently the largest encyclopedia publicly available on the Web. In addition to keyword search and subject browsing, users may quickly access articles by following hyperlinks embedded within each article. The main drawback of this method is that some links to related articles could be missing from the current article. Also, a related article could not be inserted as a hyperlink if there is no term describing it within the current article. In this paper, we propose an approach for recommending related articles based on the Latent Dirichlet Allocation (LDA) algorithm. By applying the LDA on the anchor texts from each article, a set of diverse topics could be generated. An article can be represented as a probability distribution over this topic set. Two articles with similar topic distributions are considered conceptually related. We performed an experiment on the Wikipedia Selection for Schools which is a collection of 4,625 selected articles from the Wikipedia. Based on some initial evaluation, our proposed method could generate a set of recommended articles which are more relevant than the linked articles given on the test articles.en
dc.identifier.isbn978-3-88579-242-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/20426
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof9th International Conference On Innovative Internet Community Systems I2CS 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-148
dc.titleRecommending related articles in wikipedia via a topic-based modelen
dc.typeText/Conference Paper
gi.citation.endPage203
gi.citation.publisherPlaceBonn
gi.citation.startPage194
gi.conference.dateJune 15-17, 2009
gi.conference.locationJena
gi.conference.sessiontitleRegular Research Papers

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