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The efficiency and approximation rate of LSH depend on the number of generated false positive instances and false negative instances. In many domains, reducing the number of false positives is crucial. Furthermore, in some application scenarios, balancing false positives and false negatives is favored. To address these problems, in this paper we propose Personalized Locality Sensitive Hashing (PLSH), where a new banding scheme is embedded to tailor the number of false positives, false negatives, and the sum of both. PLSH is implemented in parallel using MapReduce framework to deal with similarity joins on large scale data. Experimental studies on real and simulated data verify the efficiency and effectiveness of our proposed PLSH technique, compared with state-of-the-art methods.<\/jats:p>","DOI":"10.1155\/2015\/217216","type":"journal-article","created":{"date-parts":[[2015,4,30]],"date-time":"2015-04-30T17:03:13Z","timestamp":1430413393000},"page":"1-13","source":"Crossref","is-referenced-by-count":6,"title":["MapReduce Based Personalized Locality Sensitive Hashing for Similarity Joins on Large Scale Data"],"prefix":"10.1155","volume":"2015","author":[{"given":"Jingjing","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Xiamen University, Xiamen 361005, China"},{"name":"Shenzhen Research Institute of Xiamen University, Shenzhen 518058, China"}]},{"given":"Chen","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Xiamen University, Xiamen 361005, China"},{"name":"Shenzhen Research Institute of Xiamen University, Shenzhen 518058, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541884"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.06.002"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1002\/asi.10170"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.11.020"},{"issue":"1-2","key":"6","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.14778\/1920841.1920992","volume":"3","year":"2010","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"3","key":"9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.14778\/2078331.2078340","volume":"5","year":"2011","journal-title":"Proceedings of the VLDB Endowment"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.10.018"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.11.081"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.12.003"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1999.1690"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.04.018"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1145\/2000824.2000825"},{"year":"2011","key":"22"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.07.136"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.12.061"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.03.012"},{"year":"2012","key":"26"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2015\/217216.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2015\/217216.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2015\/217216.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,23]],"date-time":"2017-06-23T06:40:51Z","timestamp":1498200051000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cin\/2015\/217216\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":17,"alternative-id":["217216","217216"],"URL":"https:\/\/doi.org\/10.1155\/2015\/217216","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2015]]}}}