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Design of Personalized News Comments Recommendation System

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Data Science (ICDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9208))

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Abstract

Nowadays people spend lots of time on browsing news on the Internet. News comment as one of the most common things that people find on the website, is earning more attention than before. News comments have significant impacts on people’s decision and behavior as news itself. People find that they are always overwhelmed by massive comments and valuable comments are drowned in large amounts of uninteresting comments. This paper presents a multi-dimensional classification system and the personalized recommendation system of news comments, which aims to provide comments classification and personalized recommendation services. With this system, users will get a better users experience and get a comprehensive view of the news and comments with cheaper time cost.

Supported by National Grand Fundamental Research 973 Program of China under Grant No. 2013CB329605; Key Project of Science and Technology in Henan Province (2014) under Grant No. 144300510001; Transformation Project of Scientific and Technological Achievements in Henan Province (2014) under Grant No. 142201210009; Chinese Universities Scientific Fund (BUPT2014RC0701); BUPT (Beijing University of Posts and Telecommunications) Undergraduate Innovation Research Fund.

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References

  1. By the counts of discussion. Tecent coral news. http://www.qq.com/coral/coralindex/indexCoral_new.htm

  2. ICTCLAS. http://ictclas.org. Accessed 10 September 2009

  3. Jakkula, V.: Tutorial on Support Vector

    Google Scholar 

  4. Yu, H., Kim, S.: SVM Tutorial: Classification, Regression, and Ranking. Handbook of Natural Computing. Springer, Berlin (2009)

    Google Scholar 

  5. Fan, Y., Shen, Y., Mai, J.: Study of the model of e-commerce personalized recommendation system based on data mining

    Google Scholar 

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Acknowledgements

Thanks for the valuable comments from Ruifang Liu and technical discussion with Yongjiang Zhao, Qinlong Wang.

Author information

Authors and Affiliations

  1. Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China

    Ruisheng Shi

  2. School of Humanities, Beijing University of Posts and Telecommunications, Beijing, China

    Ruisheng Shi

  3. School of Network Education, Beijing University of Posts and Telecommunications, Beijing, China

    Lina Lan

  4. International School, Beijing University of Posts and Telecommunications, Beijing, China

    Mingnan Zhou, Zhaozhen Xu, Yuan He & Yiyi Zhou

Authors
  1. Mingnan Zhou
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  2. Ruisheng Shi
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  3. Zhaozhen Xu
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  4. Yuan He
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  5. Yiyi Zhou
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  6. Lina Lan
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Corresponding author

Correspondence to Ruisheng Shi .

Editor information

Editors and Affiliations

  1. University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Xi'an Jiaotong University, Xi'an Jiaotong, China

    Wei Huang

  3. Chinese Academy of Sciences, Beijing, China

    Yong Shi

  4. University of Illinois Chicago, CHICAGO, Illinois, USA

    Philip S. Yu

  5. Fudan University, Shanghai, China

    Yangyong Zhu

  6. Research Center on Fictitious Econo, Chinese Academy of Sciences, Beijing, China

    Yingjie Tian

  7. University of Technology, Sydney, Australia

    Peng Zhang

  8. Victoria University, Melbourne, Victoria, Australia

    Jing He

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© 2015 Springer International Publishing Switzerland

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Zhou, M., Shi, R., Xu, Z., He, Y., Zhou, Y., Lan, L. (2015). Design of Personalized News Comments Recommendation System. In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-24474-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24473-0

  • Online ISBN: 978-3-319-24474-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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