Recommending related microblogs: A comparison between topic and WordNet based approaches

Chen, X; Li, L; Xiao, H; Xu, G; Yang, Z; Kitsuregawa, M

Recommending related microblogs: A comparison between topic and WordNet based approaches

Chen, X Li, L Xiao, H Xu, G

Yang, Z Kitsuregawa, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the National Conference on Artificial Intelligence, 2012, 3 pp. 2417 - 2418
Issue Date:: 2012-11-07

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Field	Value	Language
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Li, L	en_US
dc.contributor.author	Xiao, H	en_US
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.contributor.author	Yang, Z	en_US
dc.contributor.author	Kitsuregawa, M	en_US
dc.date.issued	2012-11-07	en_US
dc.identifier.citation	Proceedings of the National Conference on Artificial Intelligence, 2012, 3 pp. 2417 - 2418	en_US
dc.identifier.isbn	9781577355687	en_US
dc.identifier.uri	http://hdl.handle.net/10453/30913
dc.description.abstract	Computing similarity between short microblogs is an important step in microblog recommendation. In this paper, we investigate a topic based approach and a WordNet based approach to estimate similarity scores between microblogs and recommend top related ones to users. Empirical study is conducted to compare their recommendation effectiveness using two evaluation measures. The results show that the WordNet based approach has relatively higher precision than that of the topic based approach using 548 tweets as dataset. In addition, the Kendall tau distance between two lists recommended by WordNet and topic approaches is calculated. Its average of all the 548 pair lists tells us the two approaches have the relative high disaccord in the ranking of related tweets. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.	en_US
dc.relation.ispartof	Proceedings of the National Conference on Artificial Intelligence	en_US
dc.title	Recommending related microblogs: A comparison between topic and WordNet based approaches	en_US
dc.type	Conference Proceeding
utslib.citation.volume	3	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Toronto
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	3	en_US

Abstract:

Computing similarity between short microblogs is an important step in microblog recommendation. In this paper, we investigate a topic based approach and a WordNet based approach to estimate similarity scores between microblogs and recommend top related ones to users. Empirical study is conducted to compare their recommendation effectiveness using two evaluation measures. The results show that the WordNet based approach has relatively higher precision than that of the topic based approach using 548 tweets as dataset. In addition, the Kendall tau distance between two lists recommended by WordNet and topic approaches is calculated. Its average of all the 548 pair lists tells us the two approaches have the relative high disaccord in the ranking of related tweets. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

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http://hdl.handle.net/10453/30913