{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:34:22Z","timestamp":1763458462935,"version":"3.45.0"},"reference-count":48,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T00:00:00Z","timestamp":1469404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Science Foundation","award":["CNS-1126619, IIS-121302, and CNS-1461926"],"award-info":[{"award-number":["CNS-1126619, IIS-121302, and CNS-1461926"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2017,1,31]]},"abstract":"<jats:p>The cloud service marketplace (CSM) is an exploratory project aiming to provide \u201can AppStore for Services.\u201d It is an intelligent online marketplace that facilitates service discovery and acquisition for enterprise customers. Traditional service discovery and acquisition are time-consuming. In the era of OneClick Checkout and pay-as-you-go service plans, users expect services to be purchased online efficiently and conveniently. However, as services are complex and different from software apps, the currently prevailing App Store based on keyword search is inadequate for services.<\/jats:p>\n                  <jats:p>\n                    In CSM, exploring and configuring services are an iterative process. Customers provide their requirements in natural language and interact with the system through questioning and answering. Learning from the input, the system can incrementally clarify users\u2019 intention, narrow down the candidate services, and profile the configuration information for the candidates at the same time. CSM\u2019s back end is built around the\n                    <jats:italic toggle=\"yes\">Services Knowledge Graph (SKG)<\/jats:italic>\n                    and leverages data mining technologies to enable the semantic understanding of customers\u2019 requirements. To quantitatively assess the value of CSM, empirical evaluation on real and synthetic datasets and case studies are given to demonstrate the efficacy and effectiveness of the proposed system.\n                  <\/jats:p>","DOI":"10.1145\/2894759","type":"journal-article","created":{"date-parts":[[2016,7,26]],"date-time":"2016-07-26T09:27:29Z","timestamp":1469525249000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["CSM"],"prefix":"10.1145","volume":"8","author":[{"given":"Yexi","family":"Jiang","sequence":"first","affiliation":[{"name":"Nanjing University of Posts and Telecommunications &amp; Florida International University, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang-Shing","family":"Perng","sequence":"additional","affiliation":[{"name":"IBM T. J. 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