Current Science

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The process of creating condensed version of given text document by collecting only the important information in it is called abstractive summarization. This involves structuring the information into sentences which are simple and easy to understand. This article presents the analytical study of the process that generates abstractive summary using unified model with attribute based information extraction (IE) rules and class based templates. Classification of the document into several categories is achieved by term frequency/ inverse document frequency (TF/IDF) rules. To generate the information intensive summaries, we use templates for sentence generation. The IE rules are designed to address the complexities involved in Indian regional languages. This paper statistically analyzes the adaptation of the methodology over multiple Indian languages and many document categories. Comparisons between abstractive and extractive summaries are also presented.

Keywords

Abstractive and Extractive Text Summarizations, Information Extraction, Language Parsing and Understanding, Template Selection, Template-Based Generation.
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