{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:17:38Z","timestamp":1760710658210},"reference-count":20,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2021,8,1]]},"DOI":"10.1587\/transinf.2020bdp0023","type":"journal-article","created":{"date-parts":[[2021,7,31]],"date-time":"2021-07-31T22:15:52Z","timestamp":1627769752000},"page":"1313-1320","source":"Crossref","is-referenced-by-count":3,"title":["Optimization and Combination of Scientific and Technological Resource Services Based on Multi-Community Collaborative Search"],"prefix":"10.1587","volume":"E104.D","author":[{"given":"Yida","family":"HONG","sequence":"first","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanlei","family":"YIN","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"GUO","sequence":"additional","affiliation":[{"name":"Yunnan Electrical Power Research Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaobao","family":"LIU","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","unstructured":"[1] Central government portal, \u201cSeveral opinions on accelerating the development of science and technology service industry,\u201d http:\/\/www.gov.cn\/xinwen\/2014-10\/28\/content_2771609.html, accessed Aug. 25. 2019."},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] C. Perera and A.V. Vasilakos, \u201cA knowledge-based resource discovery for Internet of Things,\u201d Knowledge-Based Systems, vol.109, pp.122-136, Oct. 2016. 10.1016\/j.knosys.2016.06.030","DOI":"10.1016\/j.knosys.2016.06.030"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] J. Feng and N. Zhao, \u201cA New Role of Chinese Academic Librarians \u2014 The Development of Embedded Patent Information Services at Nanjing Technology University Library,\u201d J. Academic Librarianship, vol.41, no.3, pp.292-300, May 2015. 10.1016\/j.acalib.2015.03.010","DOI":"10.1016\/j.acalib.2015.03.010"},{"key":"4","unstructured":"[4] G. Dai, \u201cPromoting innovative intelligence research in race stage,\u201d J. Intelligence, vol.38, no.8, pp.771-777, 2019. Doi: 10.3772\/j.issn.1000-0135.2019.08.001. 10.3772\/j.issn.1000-0135.2019.08.001"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] J. Guo, C. Li, Y. Chen, and Y. Luo, \u201cOn-demand resource provision based on load estimation and service expenditure in edge cloud environment,\u201d J. Network and Computer Applications, vol.38, no.8, pp.771-777, 2019. 10.1016\/j.jnca.2019.102506","DOI":"10.1016\/j.jnca.2019.102506"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] D. Liu, X. Sui, L. Li, Z. Jiang, H. Wang, Z. Zhang, and Y. Zeng, \u201cA cloud service adaptive framework based on reliable resource allocation,\u201d Future Generation Computer Systems, vol.89, pp.455-463, Dec. 2018. 10.1016\/j.future.2018.05.059","DOI":"10.1016\/j.future.2018.05.059"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] X.-F. Xu, J. Hao, Y.-R. Deng, and Y. Wang, \u201cDesign optimization of resource combination for collaborative logistics network under uncertainty,\u201d Applied Soft Computing, vol.56, pp.684-691, July 2017. 10.1016\/j.asoc.2016.07.036","DOI":"10.1016\/j.asoc.2016.07.036"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] S. Baradaran, S.M.T. Fatemi Ghomi, M. Ranjbar, and S.S. Hashemin, \u201cMulti-mode renewable resource-constrained allocation in PERT networks,\u201d Applied Soft Computing, vol.12, no.1, pp.82-90, Jan. 2012. 10.1016\/j.asoc.2011.09.007","DOI":"10.1016\/j.asoc.2011.09.007"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] J. Chen, G.Q. Huang, J.-Q. Wang, and C. Yang, \u201cA cooperative approach to service booking and scheduling in cloud manufacturing,\u201d European J. Operational Research, vol.273, no.3, pp.861-873, March 2019. 10.1016\/j.ejor.2018.09.007","DOI":"10.1016\/j.ejor.2018.09.007"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] Y. Lu and X. Xu, \u201cA semantic web-based framework for service composition in a cloud manufacturing environment,\u201d J. Manufacturing Systems, vol.42, pp.69-81, Jan. 2017. 10.1016\/j.jmsy.2016.11.004","DOI":"10.1016\/j.jmsy.2016.11.004"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] J. Liao, Y. Liu, and X. Zhu, and J. Wang, \u201cAccurate sub-swarms particle swarm optimization algorithm for service composition,\u201d J. Systems and Software, vol.90, pp.191-203, April 2014. 10.1016\/j.jss.2013.11.1113","DOI":"10.1016\/j.jss.2013.11.1113"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] Y. Xie, Y. Zhu, Y. Wang, Y. Cheng, R. Xu, A.S. Sani, D. Yuan, and Y. Yang, \u201cA novel directional and non-local-convergent particle swarm optimization based workflow scheduling in cloud-edge environment,\u201d Future Generation Computer Systems, vol.97, pp.361-378, Aug. 2019. 10.1016\/j.future.2019.03.005","DOI":"10.1016\/j.future.2019.03.005"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] Y. Chen, L. Li, X. Zhao, J. Xiao, Q. Wu, and Y. Tan, \u201cSimplified hybrid fireworks algorithm,\u201d Knowledge-Based Systems, vol.173, pp.128-139, June 2019. 10.1016\/j.knosys.2019.02.029","DOI":"10.1016\/j.knosys.2019.02.029"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] J. Zhou and X. Yao, \u201cMulti-population parallel self-adaptive differential artificial bee colony algorithm with application in large-scale service composition for cloud manufacturing,\u201d Applied Soft Computing, vol.56, pp.379-397, July 2017. 10.1016\/j.asoc.2017.03.017","DOI":"10.1016\/j.asoc.2017.03.017"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[15] P. Lv, L. Yuan, and J. Zhang, \u201cCloud theory-based simulated annealing algorithm and application,\u201d Engineering Applications of Artificial Intelligence, vol.22, no.4-5, pp.742-749, June 2009. 10.1016\/j.engappai.2009.03.003","DOI":"10.1016\/j.engappai.2009.03.003"},{"key":"16","unstructured":"[16] F. Tao, L. Zhang, H. Gua, Y.-L. Luo, and L. Ren, \u201cTypical characteristics of cloud manufacturing and several key issues of cloud service composition,\u201d Computer Integrate Manufacturing Systems, Fundamentals, vol.17, no.4, pp.477-486, 2011."},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] A. Strunk, \u201cQoS-aware service composition: a survey,\u201d IEEE. Proc. 8th IEEE European Conference Web Services, Washington, D.C., USA, pp.67-74, Dec. 2010. 10.1109\/ECOWS.2010.16","DOI":"10.1109\/ECOWS.2010.16"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] F. Ning, W. Zhou, F. Zhang, Q. Yin, and X. Ni, \u201cThe architecture of cloud manufacturing and its key technologies research,\u201d IEEE Computer Society, Proceeding 2011 IEEE Int. Conf. Cloud Computing and Intelligence Systems, Washington, D.C., USA, pp.259-263, Sept. 2011. 10.1109\/CCIS.2011.6045071","DOI":"10.1109\/CCIS.2011.6045071"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[19] L. Zeng, B. Bentallah, A.H.H. Ngu, M. Dumas, J. Kalagnanam, and H. Chang, \u201cQoS-aware middleware for web services composition,\u201d IEEE Trans. Softw. Eng., vol.30, no.5, pp.311-327, May 2004. 10.1109\/TSE.2004.11","DOI":"10.1109\/TSE.2004.11"},{"key":"20","doi-asserted-by":"publisher","unstructured":"[20] F. Tao, D. Zhao, and Y. Hu, \u201cCorrelation-aware resource service composition and optimal-selection in manufacturing grid,\u201d European J. Operational Research, vol.201, no.1, pp.129-143, Feb. 2010. 10.1016\/j.ejor.2009.02.025","DOI":"10.1016\/j.ejor.2009.02.025"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E104.D\/8\/E104.D_2020BDP0023\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,7]],"date-time":"2021-08-07T06:14:47Z","timestamp":1628316887000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E104.D\/8\/E104.D_2020BDP0023\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,1]]},"references-count":20,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2020bdp0023","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,1]]},"article-number":"2020BDP0023"}}