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dc.contributor.authorChai, Kevin
dc.contributor.authorWu, Chen
dc.contributor.authorPotdar, Vidyasagar
dc.contributor.authorHayati, Pedram
dc.contributor.editorKevin Wong
dc.contributor.editorLance Fung
dc.contributor.editorHussein Abbass
dc.date.accessioned2017-01-30T13:32:00Z
dc.date.available2017-01-30T13:32:00Z
dc.date.created2012-02-23T20:00:57Z
dc.date.issued2011
dc.identifier.citationChai, Kevin and Wu, Chen and Potdar, Vidyasagar and Hayati, Pedram. 2011. Automatically measuring the quality of user generated content in forums, in Kevin Wong, Lance Fung and Hussein Abbass (ed), AI 2011: Advances in Artificial Intelligence, Proceedings of 24th Australasian Joint Conference, Dec 5-8 2011, pp. 51-60. Heidelberg: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/32636
dc.identifier.doi10.1007/978-3-642-25832-9_6
dc.description.abstract

The amount of user generated content on the Web is growing and identifying high quality content in a timely manner has become a problem. Many forums rely on its users to manually rate content quality but this often results in gathering insuffcient rating. Automated quality assessment models have largely evaluated linguistic features but these techniques are less adaptive for the diverse writing styles and terminologies used by dierent forum communities. Therefore, we propose a novel model that evaluates content, usage, reputation, temporal and structural features of user generated content to address these limitations. We employed a rule learner, a fuzzy classier and Support Vector Machines to validate our model on three operational forums. Our model outperformed the existing models in our experiments and we veried that our performance improvements were statistically signicant.

dc.publisherSpringer
dc.subjectuser generated content
dc.subjectforums
dc.subjectcontent quality assessment
dc.titleAutomatically measuring the quality of user generated content in forums
dc.typeConference Paper
dcterms.source.startPage51
dcterms.source.endPage60
dcterms.source.titleProceedings of the 24th Australasian joint conference on artificial intelligence (AI 2011)
dcterms.source.seriesProceedings of the 24th Australasian joint conference on artificial intelligence (AI 2011)
dcterms.source.isbn978-3-642-25831-2
dcterms.source.conference24th Australasian Joint Conference on Artificial Intelligence (AI 2011)
dcterms.source.conference-start-dateDec 5 2011
dcterms.source.conferencelocationPerth, Australia
dcterms.source.placeHeidelberg
curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusFulltext not available


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