Optimization and Combination of Scientific and Technological Resource Services Based on Multi-Community Collaborative Search

Yida HONG  Yanlei YIN  Cheng GUO  Xiaobao LIU  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E104-D   No.8   pp.1313-1320
Publication Date: 2021/08/01
Publicized: 2021/05/06
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2020BDP0023
Type of Manuscript: Special Section PAPER (Special Section on Computational Intelligence and Big Data for Scientific and Technological Resources and Services)
Category: 
Keyword: 
scientific and technological services,  evaluative system,  hybrid optimal combined model,  multi-community collaborative search,  maximum efficiency of combination,  

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Summary: 
Many scientific and technological resources (STR) cannot meet the needs of real demand-based industrial services. To address this issue, the characteristics of scientific and technological resource services (STRS) are analyzed, and a method of the optimal combination of demand-based STR based on multi-community collaborative search is then put forward. An optimal combined evaluative system that includes various indexes, namely response time, innovation, composability, and correlation, is developed for multi-services of STR, and a hybrid optimal combined model for STR is constructed. An evaluative algorithm of multi-community collaborative search is used to study the interactions between general communities and model communities, thereby improving the adaptive ability of the algorithm to random dynamic resource services. The average convergence value CMCCSA=0.00274 is obtained by the convergence measurement function, which exceeds other comparison algorithms. The findings of this study indicate that the proposed methods can preferably reach the maximum efficiency of demand-based STR, and new ideas and methods for implementing demand-based real industrial services for STR are provided.