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Recommendation system based on semantic scholar mining and topic modeling on conference publications

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Abstract

Recommendation systems are of great assistance to online in computer science in various aspects of the Internet portals such as social networks and library websites. There are several approaches to implement recommendation systems. Latent Dirichlet allocation (LDA) is one of the popular techniques in topic modeling. Recently, researchers have proposed many approaches based on recommendation systems and LDA. Regarding the importance of the subject, in this paper, we discover the trends of the topics and find a relationship between LDA topics and Scholar-Context-documents. We apply probabilistic topic modeling based on Gibbs sampling algorithms for semantic mining from eight conference publications in computer science from the DBLP dataset. Based on the obtained experimental results, our semantic framework can be effective to help organizations to better organize these conferences and cover future research topics.

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Acknowledgements

This article has been awarded by the National Natural Science Foundation of China (61941113, 81674099, 61502233), the Fundamental Research Fund for the Central Universities (30918015103, 30918012204), Nanjing Science and Technology Development Plan Project (201805036), and “13th Five-Year” equipment field fund (61403120501), China Academy of Engineering Consulting Research Project(2019-ZD-1-02-02).

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Authors and Affiliations

  1. School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, 210094, China

    Hamed Jelodar, Yongli Wang, Mahdi Rabbani, Ruxin Zhao, Seyedvalyallah Ayobi, Peng Hu & Isma Masood

  2. Science and Technology on Complex Systems Simulation Laboratory, Beijing, 100101, China

    Gang Xiao

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  1. Hamed Jelodar
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  2. Yongli Wang
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  3. Gang Xiao
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  4. Mahdi Rabbani
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  7. Peng Hu
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  8. Isma Masood
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Correspondence to Hamed Jelodar or Yongli Wang.

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Hamed Jelodar, Yongli Wang, Gang Xiao, Mahdi Rabbani, Ruxin Zhao, Seyedvalyallah Ayobi, Peng Hu, and Isma Masood declare no conflict of interest directly related to the submitted work.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Jelodar, H., Wang, Y., Xiao, G. et al. Recommendation system based on semantic scholar mining and topic modeling on conference publications. Soft Comput 25, 3675–3696 (2021). https://doi.org/10.1007/s00500-020-05397-3

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