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Automatic text summarization in engineering information management

Zhan, Jiaming, Loh, Han Tong, Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940 and Sun, Aixin 2007. Automatic text summarization in engineering information management. Presented at: 10th International Conference on Asian Digital Libraries (ICADL 2007), Hanoi, Vietnam, 10-13 December 2007. Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers: 10th International Conference on Asian Digital Libraries, ICADL 2007, Hanoi, Vietnam, December 10-13, 2007. Proceedings. Lecture Notes in Computer Science (4822) Berlin Heidelberg: Springer, pp. 347-350. 10.1007/978-3-540-77094-7_44

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Abstract

In today’s knowledge-intensive engineering environment, information management is an important and essential activity. However, existing researches of Engineering Information Management (EIM) mainly focused on numerical data such as computer models and process data. Textual data, especially the case of free texts, which constitute a significant part of engineering information, have been somewhat ignored, mainly due to their lack of structure and the noisy information contained in them. Since summarization is a process to distill important information from source documents and at the same time remove irrelevant and redundant information, it could address the obstacles for handling textual data in EIM. Moreover, text summarization could address the increasing demand to integrate information from multiple documents and reduce the time in acquiring useful information from massive textual data in the engineering domain. This paper discusses in detail the need to apply text summarization in EIM and introduces a case study in summarizing multiple online customer reviews.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Publisher: Springer
ISBN: 9783540770930
ISSN: 0302-9743
Last Modified: 25 Oct 2022 08:05
URI: https://orca.cardiff.ac.uk/id/eprint/51336

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