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International Conference on Cloud Computing and Security

ICCCS 2018: Cloud Computing and Security pp 525–536Cite as

Exploring Methods of Assessing Influence Relevance of News Articles

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11068))

Abstract

Assessing the influence relevance of a news article is a very important and novel task for news personalized recommendation services. It provides a novel functionality by additionally recommending users news articles that may not match users’ interest points but can help users make good decisions in their daily lives. Since the influence of implicit information delivered by news articles cannot be obtained literally, and meanwhile regions and industries affected by the influence of implicit information are usually not explicitly mentioned in news articles, machine-based methods lost their ability. In this paper we explore methods of assessing influence relevance of news articles by employing crowdsourcing, and the experimental results show that crowdsourcing can assess the influence relevance of news articles very well.

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Acknowledgements

This research has been supported by the Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of the Ministry of Education, China, under grant IRT13059, the National 973 Program of China under grant 2013CB329604, Outstanding Science-technology Innovation Team Program of Colleges and Universities in Jiangsu, the National Natural Science Foundation of China under grant 61229301, 61728205, 61672372, 61472211 and the US National Science Foundation under grant IIS-1115417.

Author information

Authors and Affiliations

  1. Hefei University of Technology, Hefei, 230009, Anhui, China

    Qingren Wang

  2. University of Central Arkansas, Conway, AR, 72035, USA

    Victor S. Sheng

  3. Suzhou Vocational University, Suzhou, 215104, Jiangsu, China

    Zhaobin Liu

Authors
  1. Qingren Wang
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  2. Victor S. Sheng
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  3. Zhaobin Liu
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Corresponding authors

Correspondence to Qingren Wang , Victor S. Sheng or Zhaobin Liu .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Wang, Q., Sheng, V.S., Liu, Z. (2018). Exploring Methods of Assessing Influence Relevance of News Articles. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11068. Springer, Cham. https://doi.org/10.1007/978-3-030-00021-9_47

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  • DOI: https://doi.org/10.1007/978-3-030-00021-9_47

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00020-2

  • Online ISBN: 978-3-030-00021-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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