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Automatic Text Summarization Using Importance of Sentences for Email Corpus

Abstract With the advent of Internet, the data being added online is increasing at enormous rate. Though search engines are using IR techniques to facilitate the search requests from users, the results are not effective towards the search query of the user. The search engine user has to go through certain webpages before getting at the webpage he/she wanted. This problem of Information Overload can be solved using Automatic Text Summarization. Summarization is a process of obtaining at abridged version of documents so that user can have a quick view to understand what exactly the document is about. Email threads from W3C are used in this system. Apart from common IR features like Term Frequency, Inverse Document Frequency, Term Rank, a variation of ... (more)
Created Date 2015
Contributor Nadella, Sravan (Author) / Davulcu, Hasan (Advisor) / Li, Baoxin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Subject Computer science / Data Mining / Machine Learning / Natural Language Processing / Pyramid Evaluation / Term Rank / Text Summarization
Type Masters Thesis
Extent 41 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2015
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis