creators_name: Tang, Lei creators_name: Rajan, Suju creators_name: Narayanan, Vijay K. type: conference_item datestamp: 2009-04-06 19:08:57 lastmod: 2009-05-11 09:59:14 metadata_visibility: show title: Large Scale Multi-Label Classification via MetaLabeler ispublished: pub full_text_status: public pres_type: paper abstract: The explosion of online content has made the management of such content non-trivial. Web-related tasks such as web page categorization, news filtering, query categorization, tag recommendation, etc. often involve the construction of multilabel categorization systems on a large scale. Existing multilabel classification methods either do not scale or have unsatisfactory performance. In this work, we propose MetaLabeler to automatically determine the relevant set of labels for each instance without intensive human involvement or expensive cross-validation. Extensive experiments conducted on benchmark data show that the MetaLabeler tends to outperform existing methods. Moreover, MetaLabeler scales to millions of multi-labeled instances and can be deployed easily. This enables us to apply the MetaLabeler to a large scale query categorization problem in Yahoo!, yielding a significant improvement in performance. date: 2009-04 pagerange: 211-211 event_title: 18th International World Wide Web Conference event_location: Madrid, Spain event_dates: April 20th-24th, 2009 event_type: conference refereed: TRUE citation: Tang, Lei and Rajan, Suju and Narayanan, Vijay K. (2009) Large Scale Multi-Label Classification via MetaLabeler. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain. document_url: http://www2009.eprints.org/22/1/p211.pdf document_url: http://www2009.eprints.org/22/2/www09-multilabel.pptx