Voting Models for Summary Extraction from Text Documents

Yogan , Jaya Kumar and Goh, Ong Sing and Mohd Khanapi, Abd Ghani and Naomie, Salim and Ameer Tawfik, Albaham (2014) Voting Models for Summary Extraction from Text Documents. In: International Conference on Information, Management Science andApplications (ICIMSA2014), 28-30 Oct 2014, Beijing, China.

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Electronic information – web pages, text documents, etc. are rapidly expanding due to the exponential growth of the World Wide Web (WWW). Information which are available through online search often provide readers with large collection of texts. Although easy access to online information had made great impact to the people, on the other hand, it has also caused them problem in facing information overload. Providing a solution to digest various information sources is indeed necessary to treat such problem. Especially in the case concerning online text sources, one study which is being actively researched is the field of automatic text summarization. In this paper, we propose the use of voting models, an effective approach in ranking aggregates tasks, to treat text summarization. Here, we will discuss how voting models can be adapted to the task of sentence ranking to generate text summaries.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User: YOGAN JAYA KUMAR
Date Deposited: 05 Nov 2014 11:49
Last Modified: 28 May 2015 04:33
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