{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T05:30:38Z","timestamp":1706765438671},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Identifying the interesting places through GPS\ntrajectory mining has been well studied based on the visitor\u2019s\nfrequency. However, the places popularity estimation\nbased on the trajectory analysis has not been explored yet.\nThe limitation in the majority of the traditional popularity\nestimation and place user-rating based methods is that all\nthe participants are given the same importance. In reality,\nit heavily depends on the visitor\u2019s category, for example,\ninternational visitors make distinct impact on popularity.\nThe proposed method maintains a registry to keep the information\nabout the visited users, their stay time and the\ntravel distance from their home location. Depending on\nthe travel nature the visitors are labeled as native, regional\nand tourist for each place in question. It considers the fact\nthat the higher stay in a place is an implicit measure of the\ngreater likings. Theweighted frequency is eventually fuzzified and applied rule based fuzzy inference system (FIS) to\ncompute popularity of the places in terms of the ratings\n\u2208 [0, 5]. We have evaluated the proposed method using a\nlarge real road GPS trajectory of 182 users for identifying\nthe ratings for the collected 26807 point of interests (POI)\nin Beijing (China).<\/jats:p>","DOI":"10.1515\/comp-2016-0002","type":"journal-article","created":{"date-parts":[[2016,2,24]],"date-time":"2016-02-24T20:59:02Z","timestamp":1456347542000},"page":"8-24","source":"Crossref","is-referenced-by-count":1,"title":["Popularity estimation of interesting locations from visitor\u2019s\ntrajectories using fuzzy inference system"],"prefix":"10.1515","volume":"6","author":[{"given":"Shivendra","family":"Tiwari","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Delhi Bharti Building , Hauzkhas , New Delhi , 110016 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saroj","family":"Kaushik","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Delhi Bharti Building , Hauzkhas , New Delhi , 110016 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2016,2,23]]},"container-title":["Open Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/view\/journals\/comp\/6\/1\/article-p8.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0002\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0002\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T08:57:11Z","timestamp":1651049831000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0002\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,2,22]]},"published-print":{"date-parts":[[2016,1,1]]}},"alternative-id":["10.1515\/comp-2016-0002"],"URL":"https:\/\/doi.org\/10.1515\/comp-2016-0002","relation":{},"ISSN":["2299-1093"],"issn-type":[{"value":"2299-1093","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,1]]}}}