Concept Mining using Conceptual Ontological Graph (COG)

Concept mining (CM) is the area of exploring and finding links, associations, relationships, and patterns among huge collections of information. In this paper, we propose concept-based text representation, with an emphasis on using the proposed representation in different application s such as information retrieval, text summarization, and question answering. This work presents a new paradigm for concept mining by extracting the concept-based information from a raw text. At the text representation level, we introduce a sentence based conceptual ontological representation that builds concept-based representations for the whole document. A new concept-based similarity measure is proposed to measure the similarity of texts based on their meaning. The proposed approach is domain independent and it could be applied to general domain applications. The proposed approach has been applied to the domain of information retrieval and preliminary results are promising, and give an affirmation for proceeding in the right directions of this research.