An Approach to Semantic Indexing Based on Tolerance Rough Set Model

摘要

In this article we propose a general framework incorporating semantic indexing and search of texts within scientific document repositories, where document representation may include, excepts the content, some additional document meta-data, citations and semantic information. Our idea is based on application of Tolerance Rough Set Model, semantic information extracted from source text and domain ontology to approximate concepts associated with documents and to enrich the vector representation. We present the experiment performed over the freely accessed biomedical research articles from Pubmed Cetral (PMC) portal. The experimental results are showing the advantages of the proposed solution.