Recommendation for Cross-Disciplinary Collaboration Based on Potential Research Field Discovery

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

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

    Abstract

    In recent years, cross-disciplinary scientific collaboration has been proved to be promising for both research practice and innovation. Lots of efforts have been spent in collaboration recommendation. However, the cross-disciplinary information is hidden in tons of publications, and the relationships between different fields are complicated, which make it challengeable recommending cross-disciplinary collaboration for a specific researcher. In this paper, a novel cross-disciplinary collaboration recommendation method (CDCR) that unearths the common cross-disciplinary collaboration patterns and historical scientific field preferences of authors is proposed to recommend potential cross-disciplinary research collaboration. In CDCR, a research field discovery algorithm is designed to classify scientific topics obtained from the publications into the correct field automatically. Then, the collaborative patterns are studied through analyzing the composition fields and the corresponding percentage of all publications. Furthermore, we investigate the common correlation of different research fields. Based on the common correlation and the researcher's specific pattern, the most valuable fields will be listed by CDCR. The effectiveness of our approach is evaluated based on a real academic dataset.

    Original languageEnglish
    Title of host publicationProceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages349-354
    Number of pages6
    ISBN (Electronic)9781538610725
    DOIs
    Publication statusPublished - 2017 Sep 6
    Event5th International Conference on Advanced Cloud and Big Data, CBD 2017 - Shanghai, China
    Duration: 2017 Aug 132017 Aug 16

    Other

    Other5th International Conference on Advanced Cloud and Big Data, CBD 2017
    CountryChina
    CityShanghai
    Period17/8/1317/8/16

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    Keywords

    • Cross-disciplinary
    • Data mining
    • Research field discovery
    • Scientific collaboration

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Hardware and Architecture
    • Information Systems and Management

    Cite this

    Liang, W., Zhou, X., Huang, S., Hu, C., & Jin, Q. (2017). Recommendation for Cross-Disciplinary Collaboration Based on Potential Research Field Discovery. In Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017 (pp. 349-354). [8026962] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBD.2017.67