Intelligent Information Retrieval Using Fuzzy Association Rule Classifier

Related Work

The primary goal of information systems is to retrieve or filter objects and classify them based on the rules described in the system. The filtering system may be classified as context based filtering or collaborative filtering (Zhou, Li, Bruza, Wu, Xuusing, & Lau, 2007; Wang, Xie, & Li, 2006). In information-filtering environments, uncertainties associated with changing interests of the user and the dynamic document stream is handled (Mostafa, Mukhopadhyay, Lam, & Palakal, 1997). The classification process is based on association rule mining technique where a rule is defined to make distinct classification. Recommendation using association rules is to predict preference for item k when the user preferred item i and j, by adding confidence of the association rules that have k in the result part and i or j in the condition part. Association rules capture relationships among items based on patterns of co-occurrence across transactions (Kumar & Thambidurai, 2004). The hierarchical structure is also used for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different second-level classifiers. In the hierarchical case, a model is learned to distinguish a second-level category from other categories within the same top level (Dumais & Chen, 2000).