Towards tagging and categorization for micro-blogs
|Title:||Towards tagging and categorization for micro-blogs||Authors:||Garcia Esparza, Sandra
O'Mahony, Michael P.
|Permanent link:||http://hdl.handle.net/10197/2517||Date:||30-Aug-2010||Online since:||2010-10-13T15:31:15Z||Abstract:||Abstract. Micro-blogging services are becoming very popular among users who want to share local or global news, their knowledge or their opinions on the real-time web. Lately, users are also using these services to search for information, and some services include tag or category information to better facilitate search. However, these tags are typically free-form in nature with users permitted to adopt their own conventions without restriction, which can make the set of tags noisy and sparse. A solution to this problem is to recommend tags (or categories) to users. Our work represents an initial study in the recommendation of categories for short-form messages in order to provide for better search and message filtering. In particular, we describe how such real-time web data can be used as a source of indexing and retrieval information for category recommendation. An evaluation performed on two different micro-blogging datasets indicates that promising performance is achieved by our approach.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Keywords:||Micro-blogs; Categorisation; Tagging; Recommendation||Subject LCSH:||Blogs
Recommender systems (Information filtering)
|Language:||en||Status of Item:||Peer reviewed||Conference Details:||Paper presented at the 21st National Conference on Artificial Intelligence and Cognitive Science (AICS 2010), Galway, Ireland, 30 August - 1 September, 2010|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
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