Speech tagging based improvement of the RSS polymerization news

Ying Bi, Yixin Jing, Peijun Ma, Doo Kwon Baik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 introduction of the value of P and R and the evaluation parameter, a good redundancy removing result is achieved.

Original languageEnglish
Title of host publicationProceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007
Pages1000-1004
Number of pages5
DOIs
Publication statusPublished - 2007 Dec 1
Event2007 International Conference on Computational Intelligence and Security, CIS'07 - Harbin, Heilongjiang, China
Duration: 2007 Dec 152007 Dec 19

Other

Other2007 International Conference on Computational Intelligence and Security, CIS'07
CountryChina
CityHarbin, Heilongjiang
Period07/12/1507/12/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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    Bi, Y., Jing, Y., Ma, P., & Baik, D. K. (2007). Speech tagging based improvement of the RSS polymerization news. In Proceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007 (pp. 1000-1004). [4415498] https://doi.org/10.1109/CIS.2007.212