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Existing works mostly based on SPARQL retrieval ignore the user\u2019s specific requirements of sensor attributes. Therefore, the recommendation results cannot satisfy the user\u2019s needs. In this article, we propose a graph-based sensor recommendation model. The model mainly includes two parts: (1) Filtering nodes in data graph. In addition to using the traditional graph matching algorithm, we propose a threshold pruning algorithm to narrow the matching scope and improve the matching efficiency. (2) Recommending top- k sensors. We use the improved fast non-dominated sorting algorithm to obtain the local optimal solutions of sensor data set, and we apply the simple additive weight algorithm to characterize and sort local optional solutions. Finally, we recommend the top- k sensors to the user. By comparison, the graph-based sensor recommendation algorithm meets user\u2019s needs more than other algorithms, and experiments show that our model outperforms several baselines in terms of both response time and precision.<\/jats:p>","DOI":"10.1177\/15501477211049307","type":"journal-article","created":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T09:16:37Z","timestamp":1651914997000},"page":"155014772110493","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["A graph-based sensor recommendation model in semantic sensor network"],"prefix":"10.1177","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8592-2033","authenticated-orcid":false,"given":"Yuanyi","family":"Chen","sequence":"first","affiliation":[{"name":"Hangzhou Key Laboratory for IoT Technology and Application, Zhejiang University City College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yihao","family":"Lin","sequence":"additional","affiliation":[{"name":"Hangzhou Key Laboratory for IoT Technology and Application, Zhejiang University City College, Hangzhou, China"},{"name":"Department of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9986-0438","authenticated-orcid":false,"given":"Peng","family":"Yu","sequence":"additional","affiliation":[{"name":"Hangzhou Key Laboratory for IoT Technology and Application, Zhejiang University City College, Hangzhou, China"},{"name":"Department of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5342-1699","authenticated-orcid":false,"given":"Yanyun","family":"Tao","sequence":"additional","affiliation":[{"name":"Hangzhou Key Laboratory for IoT Technology and Application, Zhejiang University City College, Hangzhou, China"},{"name":"Department of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0386-6080","authenticated-orcid":false,"given":"Zengwei","family":"Zheng","sequence":"additional","affiliation":[{"name":"Hangzhou Key Laboratory for IoT Technology and Application, Zhejiang University City College, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2022,5,7]]},"reference":[{"key":"bibr1-15501477211049307","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2953045"},{"journal-title":"CISCO White paper, CISCO, San Jose, CA","year":"2011","author":"Evans D.","key":"bibr2-15501477211049307"},{"key":"bibr3-15501477211049307","first-page":"4087","volume":"27","author":"Huang YH","year":"2010","journal-title":"Appl Res Comput"},{"key":"bibr4-15501477211049307","doi-asserted-by":"publisher","DOI":"10.14257\/astl.2015.81.20"},{"key":"bibr5-15501477211049307","doi-asserted-by":"crossref","unstructured":"Bermudezedo M, Elsaleh T, Barnaghi P, et al. 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