Removal of Network Ambiguities through Knowledge based System Pradeep Kumar

Documents on the Internet are composed of several kinds of multimedia information when accessed for personal, entertainment, business, and scientific purposes. There are many specific content domains of interest to different communities of users. Extracting semantic relationships between entities from text documents is challenging task in information extraction. By semantics for natural language in this connection, this paper understand not just the relating of a semantic representation language to natural language but the evaluation of natural language expressions with respect to databases. Evaluating a declarative sentence (on a given reading) with respect to a database involves determining whether the sentence is true with respect to the data base, whether the sentence appropriately describes the database. Evaluating a question with respect to a database might determine what information in the database would lead to appropriate answers to the question. The implementation of a knowledge-based system that deals with the Very Large Scale requires the important consideration of several problems, including the complexity of the domain, the nature of information processing, and the automation requirements to this problem is the aim of this work. It addresses the incorporation of diverse lexical, syntactic and semantic knowledge in feature-based relation extraction using support vector machines. This paper have used the base phrase chunking information for relation extraction and have also demonstrated the use of Word Net in feature-based relation extraction to further improve the performance