Summary of FAQs from a topical forum based on the native composition structure

Authors:
Yu-Hui Tao;Shu-Chu Liu;Chih-Lung Lin
Affiliations:
Department of Information Management, National University of Kaohsiung, 700, Kaohsiung University Road, Nan-Tzu District 833, Kaohsiung 811, Taiwan, ROC;Department of Information Management, National Pingtung University of Science and Technology, 1, Shueh-Fu Road, Nei-Pu Hsiang, Pingtung County 91201, Taiwan, ROC;Department of Information Management, National Pingtung University of Science and Technology, 1, Shueh-Fu Road, Nei-Pu Hsiang, Pingtung County 91201, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 17
Cited 1

A trainable document summarizer

SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
On Chinese text retrieval

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic text structuring and summarization

Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
Text structuration leading to an automatic summary system: RAFI

Information Processing and Management: an International Journal
New Methods in Automatic Extracting

Journal of the ACM (JACM)
Document clustering for electronic meetings: an experimental comparison of two techniques

Decision Support Systems - From information retrieval to knowledge management: enabling technologies and best practices
Summarization of discussion groups

Proceedings of the tenth international conference on Information and knowledge management
Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
The Challenges of Automatic Summarization

Computer
The diversity-based approach to open-domain text summarization

Information Processing and Management: an International Journal
New Feature Sets for Summarization by Sentence Extraction

IEEE Intelligent Systems
Word identification for Mandarin Chinese sentences

COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
Toward the "at-a-glance" summary: phrase-representation summarization method

COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A Study of Chinese Text Summarization Using Adaptive Clustering of Paragraphs

CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
World wide web site summarization

Web Intelligence and Agent Systems
Automatic summarising: The state of the art

Information Processing and Management: an International Journal
Inferring strategies for sentence ordering in multidocument news summarization

Journal of Artificial Intelligence Research

Using Wikipedia concepts and frequency in language to extract key terms from support documents

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

This research improves the presentation of an automatic multiple-document summarization system, which produces the frequently asked questions (FAQs) of a topical forum. The design and findings of the proposed presentation structure based on a four-part pattern of traditional Chinese articles are presented. An experiment was designed to conduct an objective experimental analysis based on criteria consisting of compression rate, recall rate, and precision rate, as well as a subjective experimental analysis based on user acceptance in terms of the indication, readability, appropriate number of sentences, and structure of the summary. The experimental results show that the proposed summary presentation structure with both domain-terminology corpus methods produced a significantly improved summary presentation compared with the original system. Nevertheless, the FAQ summary presentation system could have used complete sentences instead of partial sentences from the original articles for improved readability.