Improving matching process in social network using implicit and explicit user information
Alsaleh, Slah, Nayak, Richi, Xu, Yue, & Chen, Lin (2011) Improving matching process in social network using implicit and explicit user information. In Du, Xiaoyong, Wenfei, Fan, & Jianmin, Wang (Eds.) Proceedings of the Asia-Pacific Web Conference (APWeb 2011) Lecture Notes in Computer Science, Springer Computer Science , Beijing,China, pp. 313-320.
Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||social matching system, recommender system, clustering users in social network|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > OTHER INFORMATION AND COMPUTING SCIENCES (089900) > Information and Computing Sciences not elsewhere classified (089999)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2011 please consult the authors|
|Deposited On:||11 Mar 2011 09:53|
|Last Modified:||21 Jul 2014 11:18|
Repository Staff Only: item control page