Using text mining for information extraction / Saliza Ramly

The growth of the Internet and the availability of very large amounts of documents online that contain valuable information, have caused the need for tools to assist the users to extract the relevant information from the bundle of information without having to read them all, and also to retrieve...

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Bibliographic Details
Main Author: Ramly, Saliza
Format: Thesis
Language:English
Published: Faculty of Computer and Mathematical Sciences 2007
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/956/1/TD_SALIZA%20RAMLY%20CS%2007_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/956/
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Summary:The growth of the Internet and the availability of very large amounts of documents online that contain valuable information, have caused the need for tools to assist the users to extract the relevant information from the bundle of information without having to read them all, and also to retrieve it in a fast and effective. An e-mail is composed of date, e-mail address, subject, body of the e-mail, and so on. It is possible for the body to include pictures, sounds, and programs, but usually the body is mainly composed of textual data. Thus, it is possible to use text mining techniques in order to analyze e-mails. The research focuses on the email of students in Faculty of Information Technology and Quantitative Sciences (FTMSK). There are three objectives of the research that have been achieved. The survey was conducted to achieve the first objective. The second objective was achieved through content analysis and website observation. Researcher was identified the basic techniques that usually used and tabulate it in form of table. A number of organizations that have been done some development on text miner as their commercial product also have been identified. Finally, the third objective of the research was achieved through the development of a tool using text mining techniques. Furthermore, the Prototyping Methodology is chosen in order to develop the system. The researcher identified appropriate techniques from the past researches and existing text mining tool. As a result, categorization, clustering and summarization techniques was selected and applied for Text Mining Application Tool, TMAT development.