A combined method for mitigating sparsity problem in tag recommendation
Contribuinte(s) |
Pasi, Gabriella Pedrycz, Witold |
---|---|
Data(s) |
2014
|
Resumo |
Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods. |
Formato |
application/pdf |
Identificador | |
Publicador |
Computer Society Press |
Relação |
http://eprints.qut.edu.au/62624/1/hicss-2014-camera-ready-paper-166.pdf http://www.computer.org/csdl/proceedings/hicss/index.html DOI:10.1109/HICSS.2014.120 Djuana, Endang, Xu, Yue, Li, Yuefeng, & Josang, Audun (2014) A combined method for mitigating sparsity problem in tag recommendation. In Pasi, Gabriella & Pedrycz, Witold (Eds.) Proceedings of the 47th Annual Hawaii International Conference on System Sciences, Computer Society Press, Hilton Waikoloa, Big Island, Hawaii, US, pp. 906-915. http://purl.org/au-research/grants/ARC/LP0776400 |
Direitos |
Copyright 2013 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #080000 INFORMATION AND COMPUTING SCIENCES #080109 Pattern Recognition and Data Mining #080704 Information Retrieval and Web Search #Tag recommendation #Sparsity problem #Tags set expansion #Folksonomy #Ontology #Collaborative filtering |
Tipo |
Conference Paper |