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Conference Paper: Fast and semantic measurements on collaborative tagging quality

TitleFast and semantic measurements on collaborative tagging quality
Authors
Issue Date2016
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 20th Pacific-Asia Conference (PAKDD 2016), Auckland, New Zealand, 19-22 April 2016. In Conference Proceedings, 2016, v. 9652, p. 363-375 How to Cite?
AbstractThis paper focuses on the problem of tagging quality evaluation in collaborative tagging systems. By investigating the dynamics of tagging process, we find that high frequency tags almost cover the main aspects of a resource content and can be determined stable much earlier than a whole tag set. Motivated by this finding, we design the swapping index and smart moving index on tagging quality. We also study the correlations in tag usage and propose the semantic measurement on tagging quality. The proposed methods are evaluated against real datasets and the results show that they are more efficient than previous methods, which are appropriate for a large number of web resources. The effectiveness is justified by the results in tag based applications. The light weight metrics bring a little loss on the performance, while the semantic metric is better than current methods. © Springer International Publishing Switzerland 2016.
DescriptionLNCS v. 9652 entitled: Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part 2
Persistent Identifierhttp://hdl.handle.net/10722/232185
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorSun, Y-
dc.contributor.authorSun, H-
dc.contributor.authorCheng, RCK-
dc.date.accessioned2016-09-20T05:28:18Z-
dc.date.available2016-09-20T05:28:18Z-
dc.date.issued2016-
dc.identifier.citationThe 20th Pacific-Asia Conference (PAKDD 2016), Auckland, New Zealand, 19-22 April 2016. In Conference Proceedings, 2016, v. 9652, p. 363-375-
dc.identifier.isbn978-3-319-31749-6-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/232185-
dc.descriptionLNCS v. 9652 entitled: Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part 2-
dc.description.abstractThis paper focuses on the problem of tagging quality evaluation in collaborative tagging systems. By investigating the dynamics of tagging process, we find that high frequency tags almost cover the main aspects of a resource content and can be determined stable much earlier than a whole tag set. Motivated by this finding, we design the swapping index and smart moving index on tagging quality. We also study the correlations in tag usage and propose the semantic measurement on tagging quality. The proposed methods are evaluated against real datasets and the results show that they are more efficient than previous methods, which are appropriate for a large number of web resources. The effectiveness is justified by the results in tag based applications. The light weight metrics bring a little loss on the performance, while the semantic metric is better than current methods. © Springer International Publishing Switzerland 2016.-
dc.languageeng-
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/-
dc.relation.ispartofLecture Notes in Computer Science-
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-31750-2_29-
dc.titleFast and semantic measurements on collaborative tagging quality-
dc.typeConference_Paper-
dc.identifier.emailCheng, RCK: ckcheng@cs.hku.hk-
dc.identifier.authorityCheng, RCK=rp00074-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-319-31750-2_29-
dc.identifier.scopuseid_2-s2.0-84987936715-
dc.identifier.hkuros265280-
dc.identifier.volume9652-
dc.identifier.spage363-
dc.identifier.epage375-
dc.publisher.placeGermany-
dc.customcontrol.immutablesml 161117-

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