International Journal of Intelligent Systems

    IJIS is the only national membership organization that brings together the innovative thinking of the private sector and the practitioners, national practice associations, and academic organizations that are working to solve public sector information and technology challenges. IJIS Institute advocates for policies, processes, and information sharing standards that impact our safety and security, builds knowledge on behalf of our stakeholder groups, and connects the organizations and leaders within the communities of interest. The IJIS Institute was founded in 2001 as the Integrated Justice Information Systems Institute as a result of the U.S. Department of Justice’s interest in raising private sector participation in the advancement of national initiatives affecting justice and public safety, and more recently homeland security. Read more about IJIS Institute's history here. Today, the IJIS Institute provides a trusted forum within and across our areas of focus where resources are developed, collaboration is encouraged, and public-sector stakeholders can realize the benefits of technology and the power of information to keep our communities safe, healthy, and thriving. We represent the leading technology solution providers serving justice, public safety, homeland security, and related sectors. The IJIS Institute provides assistance to government agencies by bringing industry to the table in a constructive role, and continuing to drive toward achieving high regard for the companies that are dedicated to helping the public sector find high-value solutions. The IJIS Institute is funded through a combination of federal grants, industry contributions, and partnership agreements.

    Author Distribution

    Top Authors ( author's name : number of papers / citations )

    2015
    Zeshui Xu: 2 / 87
    Xunjie Gou: 1 / 62
    Peijia Ren: 1 / 62
    Francisco J. Quesada: 1 / 34
    IváN Palomares: 1 / 34
    Luis MartíNez-LóPez: 1 / 34
    Jorge Castro: 1 / 34
    Jie Lu: 2 / 30
    Francisco J. Quesada: 1 / 28
    IváN Palomares: 1 / 28
    Jorge Castro: 1 / 28
    Luis MartíNez: 1 / 28
    Guangquan Zhang: 1 / 26
    Wei Wang: 1 / 26
    Na Zhao: 1 / 25
    Fengjun Liu: 1 / 25
    Guangquan Zhang: 1 / 20
    Montserrat GuilléN: 1 / 20
    Wei Wang: 1 / 20
    Jie Lu: 1 / 20
    2016
    Harish Garg: 1 / 203
    Xindong Peng: 1 / 108
    Yong Yang: 1 / 108
    Xindong Peng: 1 / 99
    Yong Yang: 1 / 99
    Zeshui Xu: 2 / 98
    Peijia Ren: 1 / 86
    Xiaolu Zhang: 1 / 86
    Xunjie Gou: 1 / 86
    Cuiping Wei: 1 / 31
    Chao Zhang: 1 / 31
    Rui Ren: 1 / 31
    Deyu Li: 1 / 31
    Huchang Liao: 1 / 31
    Han-Liang Huang: 1 / 27
    Henri Prade: 1 / 25
    Didier Dubois: 1 / 25
    Bernard De Baets: 1 / 14
    Lemnaouar Zedam: 1 / 14
    José M. Merigó: 2 / 14

    Publications

    Browse by Citation
    10

    A Consensus-Driven Group Recommender SystemCited by 28

    Jorge Castro,Francisco J. Quesada,Iván Palomares,Luis Martínez
    (2015)
    21

    Compatibility of Fuzzy Relations.Cited by 14

    Azzedine Kheniche,Bernard De Baets,Lemnaouar Zedam
    (2016)
    37

    An OWA-Based Model for Talent Enhancement in CricketCited by 5

    Gulfam Ahamad,S. Kazim Naqvi,M. M. Sufyan Beg
    (2016)