Implementation of 6-W based precisiation structure for text summarization using V B .net

Abstract Text summarization is an emerging research domain of Computational Linguistics. It is an important area of research in human-machine interaction, which aims at interpretation of the natural language text by machine, at a level comparable with human being. This paper presents the design of a precisiation knowledge structure for text summarization using the concept of Six W‘s on V B .NET platform. This technique aims at developing a knowledge base which is compact and aids fast and efficient storage and search, because it overcomes the drawbacks associated with the key word and key phrase based searching employed by the approaches currently in prevalence. This approach classifies the natural language in a more refined and easy manner to access six attributes, viz. 6 W’s, as opposed to the classification through parts of speech such as noun, verb etc. An illustrative example shows the efficacy of the new approach. Key words NLP, CL AI, PNL