A concept based graph model for document representation using coreference resolution

Abstract

Graph representation is an efficient way of representing text and it is used for document similarity analysis. A lot of research has been done in document similarity analysis but all of them are keyword based methods like Vector Space Model and Bag of Words. These methods do not preserve the semantics of the document. Our paper proposes a concept based graph model which follows a Triplet Representation with coreference resolution which extract the concepts in both sentence and document level. The extracted concepts are clustered using a modified DB Scan algorithm which then forms a belief network. In this paper we also propose a modified algorithm for Triplet Generation.