{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T13:34:56Z","timestamp":1648906496268},"reference-count":13,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2009,6]]},"abstract":"<jats:p> Data perturbation is a popular method to achieve privacy-preserving data mining. However, distorted databases bring enormous overheads to mining algorithms as compared to original databases. In this paper, we present the GrC-FIM algorithm to address the efficiency problem in mining frequent itemsets from distorted databases. Two measures are introduced to overcome the weakness in existing work: firstly, the concept of independent granule is introduced, and granule inference is used to distinguish between non-independent itemsets and independent itemsets. We further prove that the support counts of non-independent itemsets can be directly derived from subitemsets, so that the error-prone reconstruction process can be avoided. This could improve the efficiency of the algorithm, and bring more accurate results; secondly, through the granular-bitmap representation, the support counts can be calculated in an efficient way. The empirical results on representative synthetic and real-world databases indicate that the proposed GrC-FIM algorithm outperforms the popular EMASK algorithm in both the efficiency and the support count reconstruction accuracy. <\/jats:p>","DOI":"10.1142\/s0218001409007314","type":"journal-article","created":{"date-parts":[[2009,6,17]],"date-time":"2009-06-17T01:30:55Z","timestamp":1245202255000},"page":"825-846","source":"Crossref","is-referenced-by-count":2,"title":["MINING FREQUENT ITEMSETS IN DISTORTED DATABASES WITH GRANULAR COMPUTING"],"prefix":"10.1142","volume":"23","author":[{"given":"JINLONG","family":"WANG","sequence":"first","affiliation":[{"name":"School of Computer Engineering, Qingdao Technological University, Qingdao, Shandong 266033, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"CONGFU","family":"XU","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Zhejiang University, Hangzhou, Zhejiang 310027, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"GANG","family":"LI","sequence":"additional","affiliation":[{"name":"School of Engineering and Information Technology, Deakin University, 221 Burwood Highway, VIC 3125, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1145\/380995.381017"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001407005612"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-006-0059-1"},{"key":"rf16","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008384328214"},{"key":"rf18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1791-1_2"},{"key":"rf19","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009748302351"},{"key":"rf20","first-page":"1","author":"Pawlak Z.","journal-title":"Trans. Rough Sets"},{"key":"rf23","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001407005600"},{"key":"rf26","doi-asserted-by":"publisher","DOI":"10.1002\/1098-111X(200101)16:1<87::AID-INT7>3.0.CO;2-S"},{"key":"rf27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1791-1_5"},{"key":"rf28","first-page":"232","author":"Yao Y. Y.","journal-title":"Trans. Rough Sets"},{"key":"rf32","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(97)00077-8"},{"key":"rf33","doi-asserted-by":"publisher","DOI":"10.1007\/s005000050030"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001409007314","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T02:18:02Z","timestamp":1565144282000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001409007314"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,6]]},"references-count":13,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2009,6]]}},"alternative-id":["10.1142\/S0218001409007314"],"URL":"https:\/\/doi.org\/10.1142\/s0218001409007314","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,6]]}}}