Research Repository

Toast: a topic-oriented tag based recommender system

Xu, Guandong, Gu, Yanhui, Zhang, Yanchun and Kitsuregawa, Masaru (2011) Toast: a topic-oriented tag based recommender system. In: Web information system engineering - WISE 2011 : 12th International Conference, Sydney, Australia, October 13-14, 2011, proceedings. Bouguettaya, Athman, Hauswirth, Manfred and Liu, Ling, eds. Lecture Notes in Computer Science (6997). Springer Press, Heidelburg, Germany, pp. 158-171.

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Abstract

Social Annotation Systems have emerged as a popular application with the advance of Web 2.0 technologies. Tags generated by users using arbitrary words to express their own opinions and perceptions on various resources provide a new intermediate dimension between users and resources, which deemed to convey the user preference information. Using clustering for topic extraction and incorporating it with the capture of user preference and resource affiliation is becoming an effective practice in tag-based recommender systems. In this paper, we aim to address these challenges via a topic graph approach. We first propose a Topic Oriented Graph (TOG), which models the user preference and resource affiliation on various topics. Based on the graph, we devise a Topic-Oriented Tag-based Recommendation System (TOAST) by using the preference propagation on the graph. We conduct experiments on two real datasets to demonstrate that our approach outperforms other state-of-the-art algorithms.

Item Type: Book Section
ISBN: 9783642244339 (print) 9783642244346 (online)
Uncontrolled Keywords: ResPubID22795, tags, tagging, software engineering, data mining, knowledge discovery, interfaces, information systems, information storage, retrieval, social media
Subjects: FOR Classification > 0801 Artificial Intelligence and Image Processing
FOR Classification > 0804 Data Format
FOR Classification > 0805 Distributed Computing
SEO Classification > 8902 Computer Software and Services
Faculty/School/Research Centre/Department > School of Engineering and Science
Depositing User: VUIR
Date Deposited: 30 Nov 2012 05:35
Last Modified: 26 Aug 2013 00:12
URI: http://vuir.vu.edu.au/id/eprint/9813
DOI: https://doi.org/10.1007/978-3-642-24434-6_12
ePrint Statistics: View download statistics for this item
Citations in Scopus: 6 - View on Scopus

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