A Summarizer for Tamil Language Using Centroid Approach

Syed Sabir Mohamed and Shanmugasundaram Hariharan
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Syed Sabir Mohamed: Research Scholar, Faculty in Computer Science & Engineering, Sathyabama University, Chennai, India
Shanmugasundaram Hariharan: Department of Computer Science and Engineering, TRP Engineering College, Tiruchirappalli, India

International Journal of Information Retrieval Research (IJIRR), 2016, vol. 6, issue 1, 1-15

Abstract: Document summarization plays a vital role in the use and management of information dissemination. This paper investigates a method for the production of summaries from Tamil newspaper text document. The primary goal is to create an effective and efficient tool that is able to summarize the given text documents in a form of meaningful extract of the original text document using centroid-based algorithm. The paper focuses on generating summaries using a centroid-based algorithm, which represents group of words that are statistically important for a document. Each sentence in a document is considered as a vector in a multi-dimensional space. The sentences that are nearest to the centroid value are considered as the most important sentences. The importance of a sentence is determined by three parameters the centroid value, the positional value, and the first sentence overlap. The score for each sentence is calculated and the redundancy between the sentences is eliminated using CSIS. Finally, the sentences are ranked and the sentences with highest score values are selected as summary.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:6:y:2016:i:1:p:1-15

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