Real-time automatic tag recommendation

Yang Song, Ziming Zhuang, Huajing Li, Qiankun Zhao, Jia Li, Wang Chien Lee, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

184 Scopus citations

Abstract

Tags are user-generated labels for entities. Existing research on tag recommendation either focuses on improving its accuracy or on automating the process, while ignoring the efficiency issue. We propose a highly-automated novel framework for real-time tag recommendation. The tagged training documents are treated as triplets of (words, docs, tags), and represented in two bipartite graphs, which are partitioned into clusters by Spectral Recursive Embedding (SRE). Tags in each topical cluster are ranked by our novel ranking algorithm. A two-way Poisson Mixture Model (PMM) is proposed to model the document distribution into mixture components within each cluster and aggregate words into word clusters simultaneously. A new document is classified by the mixture model based on its posterior probabilities so that tags are recommended according to their ranks. Experiments on large-scale tagging datasets of scientific documents (CiteULike) and web pages (del.icio.us) indicate that our framework is capable of making tag recommendation efficiently and effectively. The average tagging time for testing a document is around 1 second, with over 88% test documents correctly labeled with the top nine tags we suggested.

Original languageEnglish (US)
Title of host publicationACM SIGIR 2008 - 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Proceedings
Pages515-522
Number of pages8
DOIs
StatePublished - Dec 15 2008
Event31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM SIGIR 2008 - Singapore, Singapore
Duration: Jul 20 2008Jul 24 2008

Other

Other31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM SIGIR 2008
CountrySingapore
CitySingapore
Period7/20/087/24/08

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Software

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