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Knowledge-Based Intelligent Information and Engineering Systems 1.
Vasile Palade
Robert J. Howlett
L. C. Jain
其他書名
7th International Conference, KES 2003, Oxford, UK, September 3-5, 2003, Proceedings,
出版
Springer Science & Business Media
, 2003-08-27
主題
Business & Economics / Information Management
Business & Economics / Business Mathematics
Computers / General
Computers / Artificial Intelligence / General
Computers / Business & Productivity Software / General
Computers / Computer Science
Computers / Data Science / Data Warehousing
Computers / Artificial Intelligence / Expert Systems
Computers / System Administration / Storage & Retrieval
Computers / Information Technology
Computers / Management Information Systems
Computers / Networking / General
Computers / Software Development & Engineering / General
Computers / User Interfaces
Computers / Networking / Hardware
Computers / Human-Computer Interaction (HCI)
Computers / Desktop Applications / General
Technology & Engineering / Automation
Technology & Engineering / Electronics / General
ISBN
3540408037
9783540408031
URL
http://books.google.com.hk/books?id=S5dMfq2ugKcC&hl=&source=gbs_api
EBook
SAMPLE
註釋
2.1 Text Summarization “Text summarization is the process of distilling the most important information from a source (or sources) to produce an abridged version for a particular user (or users) and task (or tasks)” [3]. Basic and classical articles in text summarization appear in “Advances in automatic text summarization” [3]. A literature survey on information extraction and text summarization is given by Zechner [7]. In general, the process of automatic text summarization is divided into three stages: (1) analysis of the given text, (2) summarization of the text, (3) presentation of the summary in a suitable output form. Titles, abstracts and keywords are the most common summaries in Academic papers. Usually, the title, the abstract and the keywords are the first, second, and third parts of an Academic paper, respectively. The title usually describes the main issue discussed in the study and the abstract presents the reader a short description of the background, the study and its results. A keyword is either a single word (unigram), e.g.: ‘learning', or a collocation, which means a group of two or more words, representing an important concept, e.g.: ‘machine learning', ‘natural language processing'. Retrieving collocations from text was examined by Smadja [5] and automatic extraction of collocations was examined by Kita et al. [1].