Temporal Text Summarization of TV Serial Excerpts Using Lingo Clustering and Lucene Summarizer

International Journal of Computer Science and Engineering

© 2015 by SSRG - IJCSE Journal

Volume 2 Issue 5

Year of Publication : 2015

Authors : Sayali Hande, Mrs. M. A. Potey

10.14445/23488387/IJCSE-V2I5P139

How to Cite?

Sayali Hande, Mrs. M. A. Potey, "Temporal Text Summarization of TV Serial Excerpts Using Lingo Clustering and Lucene Summarizer," SSRG International Journal of Computer Science and Engineering , vol. 2,  no. 5, pp. 16-22, 2015. Crossref, https://doi.org/10.14445/23488387/IJCSE-V2I5P139

Abstract:

Text summarization is an art of abstracting key contents from one or more information sources. As time is an important dimension of any information space, it is becoming harder to generate meaningful and timely summaries. While summarizing a story in terms of a timeline, a system may have to extract events and order chronologically. Hence the goal of Temporal Summarization is to develop a system that allows users to efficiently monitor the information associated with an event over time. Previous research algorithms having good speed and scalability share one important shortcoming that, none of them explicitly addresses the problem of cluster description quality. For this reason document clustering is done by using Lingo algorithm in which special emphasis is placed on the quality of cluster labels. Lucene Summarizer is used for text summarization. In many cases users have to spend their maximum time in reading the detail story of entire series of Television (TV) serial episodes which they missed. This paper focuses on a novel application used for automatic generation of meaningful temporal text summarization of missing TV serial excerpts. The user can specify the time period for the content.

Keywords:

Information Retrieval System, Lingo clustering algorithm, Singular Value Decomposition, Lucene summarizer, Temporal...

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