ONTOLOGY-BASED MODEL FOR GENERATING TEXT SEMANTIC REPRESENTATION

The explosive growth in the number of electronic documents produced daily necessitates the development of effective alternatives to explore, analyze, and discover knowledge from documents. In this paper, a new approach is proposed to analyze text and represent valuable information in an ontology-based representation form. The main objective is to propose a model that transforms an input text to semantic graph representation called Rich Semantic Graph (RSG) in which verbs and nouns of a document are represented as nodes along with edges corresponding to semantic and linguistic relations between them. The rich semantic graph can be exploited in several applications like information retrieval, text summarization, and text mining applications. This work is a part of an ongoing research to create an abstractive summary for a single input document.