Title

Automatic text summarization

Date of Publication

2005

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Allan B. Borra

Defense Panel Chair

Allan B. Borra

Defense Panel Member



Ethel Ong
Charibeth Ko Cheng

Abstract/Summary

Given an information source, Automatic Text Summarization (ATS) produces the cluster of information which is most relevant to the needs of the user. The three approaches in ATS are the shallow approach, the deeper approach, and the hybrid approach. A common problem with these approaches is that they do not have sufficient coherence. Coherence is the way the parts of the text gather together to form an integrated whole. With today's automatic text summarizers, statements are commonly non-sequitur-meaning a statement that does not follow logically from what preceded it. There is no smooth transition from one idea to another. The driving force of this research is the development of a system that will be able to summarize a given document while still maintaining coherence and salient information in the text. To do this, the system architecture integrated two main existing techniques in ATS: keyword extraction and discourse analysis based on Rhetorical Structure Theory (RST).

Keywords: automatic text summarization, natural language processing, keyword extraction, rhetorical structure theory, coherence.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU13616

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

1 v. (various foliations) : ill. (some col.) ; 28 cm.

Keywords

Natural language processing (Computer science); Artificial intelligence; Logic programming; Knowledge representation (Information theory); Coherent states

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