Collaborative Filtering-based Context-Aware Document-Clustering (CF-CAC) Technique

Publication Year:
2008
Usage 103
Abstract Views 53
Downloads 50
Repository URL:
https://aisel.aisnet.org/pacis2008/88
Author(s):
Wei, Chih-Ping; Yang, Chin-Sheng
Tags:
Document clustering; Context-aware document-clustering; Collaborative filtering; Text mining
article description
Document clustering is an intentional act that should reflect an individual's preference with regard to the semantic coherency or relevant categorization of documents and should conform to the context of a target task under investigation. Thus, effective document clustering techniques need to take into account a user's categorization context. In response, Yang & Wei (2007) propose a Context-Aware document Clustering (CAC) technique that takes into consideration a user's categorization preference relevant to the context of a target task and subsequently generates a set of document clusters from this specific contextual perspective. However, the CAC technique encounters the problem of small-sized anchoring terms. To overcome this shortcoming, we extend the CAC technique and propose a Collaborative Filtering-based Context-Aware document-Clustering (CF-CAC) technique that considers not only a target user's but also other users' anchoring terms when approximating the categorization context of the target user. Our empirical evaluation results suggest that our proposed CF-CAC technique outperforms the CAC technique.