Pattern Based Information Filtering for Author Community Generation

Neena G. Krishnan, Neena Joseph

Abstract: Pattern mining is one of the important research areas in data mining and knowledge discovery. The data mining concept is used in the field of information filtering. User?s interested information is collected using these data mining concepts. Maximum matched pattern based Topic Model provide a suitable way to analyze large number of unclassified text. Large amount of discovered patterns stop them from being effectively and efficiently used in real application, therefore selection of the most separate and representative semantic patterns from the huge amount of discovered patterns become crucial. To deal with the above mentioned problem, propose NFA based Maximum matched Pattern based Topic Modeling.Finally it enhanced to an author community model. Search document within the author community is efficient and easy.

Keywords: Topic model, information filtering, pattern mining, cluster