Thursday 25th of April 2024
 

A sentence scoring method for extractive text summarization based on Natural language queries


R.V.V Murali Krishna and Ch. Satyananda Reddy

The developments in storage devices and computer networks have given the scope for the world to become a paperless community, for example Digital news paper systems and digital library systems. A paperless community is heavily dependent on information retrieval systems. Text summarization is an area that supports the cause of information retrieval systems by helping the users to get their needed information. This paper discusses on the relevance of using traditional stoplists for text summarization and the use of Statistical analysis for sentence scoring. A new methodology is proposed for implementing the stoplist concept and statistical analysis concept based on parts of speech tagging. A sentence scoring mechanism has been developed by combining the above methodologies with semantic analysis. This sentence scoring method has given good results when applied to find out the relation between natural language queries and the sentences in a document.

Keywords: Information retrieval systems, traditional stoplists, sentence scoring, statistical analysis, semantic analysis, parts of speech tagging.

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ABOUT THE AUTHORS

R.V.V Murali Krishna
Mr. R.V.V. Murali Krishna is a faculty of information technology in G.V.P College of engineering (Autonomous), Visakhapatnam..He is currently pursuing Ph.D in Andhra University.

Ch. Satyananda Reddy
Dr. Ch. Satyananda Reddy has obtained Ph.D in Computer Science and engineering. He is a regular faculty in computer science and systems engineering department of Andhra University, Visakhapatnam. He has taught several subjects in the areas of computer science and information technology. He is specialized in Software Engineering, Software Cost Estimation, Object Oriented Analysis & Design, Web Technologies, Data Base Management Systems, and Operating Systems


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