Investigation on Application of Local Cluster Analysis and Part of Speech Tagging on Persian Text

In this research we applied Local Cluster Analysis (LCA) in tandem with Part-of-Speech tagging to monolingual task. We study different Persian POS tags and select a set of designated tags to reduce the size of our index and store the rich content of the documents. In addition, we applied LCA on the retrieved documents to detect the relevant and irrelevant documents to the user query. The clustering method is an important part in our approach. So we address the problem of building effective and meaningful clustering and evaluate different well-known and state of the art clustering methods for better efficiency and effectiveness in the proposed approach.