Title :
Speech Tagging Based Improvement of the RSS Polymerization News
Author :
Bi, Ying ; Ma, Peijun ; Jing, Yixin ; Baik, Doo-Kwon
Abstract :
Since a significant amount of redundant information causes problems like inefficiency or congestion in the existing RSS, a method using part of speech (pos) tagging to extract keywords is proposed to solve these problems. Firstly, the title of news is analyzed by using Chinese word segmentation and speech tagging system. Then, the keywords of the title are identified according to their part of speech. All of the extracted keywords are compared, categorized and stored according to the proposed criterion in this paper. In that case, all the news in the same category is identical or similar. Thus, redundant news can be hidden to users. According to the operation, statistics, comparison and analysis of system, and the
Keywords :
Computer science; Data mining; Information retrieval; Internet; Polymers; Software systems; Speech analysis; Statistical analysis; Statistics; Tagging;
Conference_Titel :
Computational Intelligence and Security, 2007 International Conference on
Conference_Location :
Harbin, China
Print_ISBN :
0-7695-3072-9
Electronic_ISBN :
978-0-7695-3072-7
DOI :
10.1109/CIS.2007.165
