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Conference Paper: iTag: Incentive-Based Tagging

TitleiTag: Incentive-Based Tagging
Authors
Issue Date2014
PublisherI E E E, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000178
Citation
The 30th IEEE International Conference on Data Engineering (ICDE), Chicago, Illinois, USA, 31 March-4 April 2014. In International Conference on Data Engineering. Proceedings, 2014, p. 1186-1189, article no. 6816737 How to Cite?
AbstractIn social tagging systems, such as Delicious1 and Flickr2, users are allowed to annotate resources (e.g., Web URLs and images) with textual descriptions called tags. Tags have proven to be invaluable building blocks in algorithms for searching, mining and recommending resources. In practice, however, not all resources receive the same attention from users, and as a result, most tags are added to the few highly-popular resources, while most of the resources receive few tags. Crucially, this incomplete tagging on resources can severely affect the effectiveness of all tagging applications. We present iTag, an incentive-based tagging system, which aims at improving tagging quality of resources, by incentivizing taggers under budget constraints. Our system is built upon traditional crowdsourcing systems such as Amazon Mechanical Turk (MTurk). In our demonstration, we will show how our system allows users to use simple but powerful strategies to significantly improve the tagging quality of resources.
Persistent Identifierhttp://hdl.handle.net/10722/201106
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLei, Sen_US
dc.contributor.authorYang, Xen_US
dc.contributor.authorMo, Len_US
dc.contributor.authorManiu, Sen_US
dc.contributor.authorCheng, CKen_US
dc.date.accessioned2014-08-21T07:13:35Z-
dc.date.available2014-08-21T07:13:35Z-
dc.date.issued2014en_US
dc.identifier.citationThe 30th IEEE International Conference on Data Engineering (ICDE), Chicago, Illinois, USA, 31 March-4 April 2014. In International Conference on Data Engineering. Proceedings, 2014, p. 1186-1189, article no. 6816737en_US
dc.identifier.isbn9781479925544-
dc.identifier.issn1084-4627-
dc.identifier.urihttp://hdl.handle.net/10722/201106-
dc.description.abstractIn social tagging systems, such as Delicious1 and Flickr2, users are allowed to annotate resources (e.g., Web URLs and images) with textual descriptions called tags. Tags have proven to be invaluable building blocks in algorithms for searching, mining and recommending resources. In practice, however, not all resources receive the same attention from users, and as a result, most tags are added to the few highly-popular resources, while most of the resources receive few tags. Crucially, this incomplete tagging on resources can severely affect the effectiveness of all tagging applications. We present iTag, an incentive-based tagging system, which aims at improving tagging quality of resources, by incentivizing taggers under budget constraints. Our system is built upon traditional crowdsourcing systems such as Amazon Mechanical Turk (MTurk). In our demonstration, we will show how our system allows users to use simple but powerful strategies to significantly improve the tagging quality of resources.-
dc.languageengen_US
dc.publisherI E E E, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000178en_US
dc.relation.ispartofInternational Conference on Data Engineering. Proceedingsen_US
dc.rightsInternational Conference on Data Engineering. Proceedings. Copyright © I E E E, Computer Society.en_US
dc.rights©2014 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleiTag: Incentive-Based Taggingen_US
dc.typeConference_Paperen_US
dc.identifier.emailManiu, S: smaniu@cs.hku.hken_US
dc.identifier.emailCheng, CK: ckcheng@cs.hku.hken_US
dc.identifier.authorityCheng, CK=rp00074en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICDE.2014.6816737-
dc.identifier.scopuseid_2-s2.0-84901753767-
dc.identifier.hkuros232985en_US
dc.identifier.spage1186, article no. 6816737-
dc.identifier.epage1189, article no. 6816737-
dc.publisher.placeUnited States-

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