Assessing Novelty of Research Articles Using Fuzzy Cognitive Maps

摘要

In this paper, we compare and analyze the novelty of a scientific paper (text document) of a specific domain. Our experiments utilize the standard Latent Dirichlet Allocation (LDA) topic modeling algorithm to filter the redundant documents and the Ontology of a specific domain which serves as the knowledge base for that domain, to generate cognitive maps for the documents. We report results based on the distance measure such as the Euclidean distance measure that analyses the divergence of the concepts between the documents.