AN IMPROVED AUTOMATIC CONTEXT SUMMARY GENERATOR SYSTEM USING DATA-MINING

Abstract

This study is designed to develop a context summary generator system using data mining technique. Despite the growing availability of electronic documents and the accessibility of desktop publishing technology, abstracts are still manually generated.
In the present paper, an automated system that can produce a summary extract of any document fed into it is developed so that a reader can take a look at the contextual interpretation of what the given document states. The system is developed using NET
Framework, MS Access, a relational database and the NET high level programming language. It is established that its application would enable readers save time and effort in finding useful information from particular articles or documents. Short versions of lengthy sentences are generated by the system using summarization techniques, while attempting to maintain their meaning