Clustering of web users using the tensor decomposed models
Rawat, Rakesh, Nayak, Richi, & Li, Yuefeng (2010) Clustering of web users using the tensor decomposed models. In De Bra, Paul, Kobsa, Alfred, & Chin, David (Eds.) User Modeling, Adaptation, and Personalization, Springer, Hilton Waikoloa Village, Big Island of Hawaii, pp. 37-39.
We propose to use the Tensor Space Modeling (TSM) to represent and analyze the user’s web log data that consists of multiple interests and spans across multiple dimensions. Further we propose to use the decomposition factors of the Tensors for clustering the users based on similarity of search behaviour. Preliminary results show that the proposed method outperforms the traditional Vector Space Model (VSM) based clustering.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Conference Paper|
|Keywords:||Tensor Space Modeling, Web Data Mining, Clustering|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Research Centres > Smart Services CRC
|Copyright Owner:||Copyright 2010 Springer|
|Copyright Statement:||This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springerlink.com|
|Deposited On:||04 Dec 2011 21:58|
|Last Modified:||05 Dec 2011 17:56|
Repository Staff Only: item control page