{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T20:34:38Z","timestamp":1769978078818,"version":"3.49.0"},"reference-count":6,"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":[[2017,4]]},"abstract":"<jats:p> FP-Growth algorithm is an algorithm of association rules that does not generate a set of candidate, so it has very high practical value in face of the rapid growth of data volume in wisdom medical treatment. Because FP-Growth is a memory-resident algorithm, it will appear to be powerless when it is used for massive data sets. The paper combines Hadoop and FP-Growth algorithm and through the actual analysis of traditional Chinese medicine (TCM) data compares the performance in two different environments of stand-alone and distributed. The experimental results show that FP-Growth algorithm has a great advantage in the processing and execution of massive data after the MapReduce parallel model, so that it will have better development prospects for intelligent medical treatment. <\/jats:p>","DOI":"10.1142\/s0218001417590054","type":"journal-article","created":{"date-parts":[[2016,8,29]],"date-time":"2016-08-29T04:30:41Z","timestamp":1472445041000},"page":"1759005","source":"Crossref","is-referenced-by-count":18,"title":["The Application of FP-Growth Algorithm Based on Distributed Intelligence in Wisdom Medical Treatment"],"prefix":"10.1142","volume":"31","author":[{"given":"Fangqin","family":"Xu","sequence":"first","affiliation":[{"name":"School of Information and Technology, Shanghai Jianqiao University, 201306, P. R. China"}]},{"given":"Haifeng","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Information and Technology, Shanghai Jianqiao University, 201306, P. R. China"},{"name":"School of Information and Technology, Shanghai DongHua University, 200051, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2017,2,2]]},"reference":[{"key":"S0218001417590054BIB003","doi-asserted-by":"publisher","DOI":"10.1142\/S0129626415500024"},{"issue":"2","key":"S0218001417590054BIB005","first-page":"153","volume":"23","author":"Ya-Han H.","year":"2015","journal-title":"Technol. Health Care Official Eur. Soci. Eng. Med."},{"key":"S0218001417590054BIB006","doi-asserted-by":"publisher","DOI":"10.14257\/ijsip.2014.7.2.13"},{"key":"S0218001417590054BIB007","first-page":"1","volume":"2015","author":"Zeng Y.","year":"2015","journal-title":"Sci. Program."},{"key":"S0218001417590054BIB008","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.631-632.125"},{"key":"S0218001417590054BIB009","doi-asserted-by":"publisher","DOI":"10.4304\/jsw.9.3.676-683"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001417590054","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T00:10:04Z","timestamp":1565136604000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001417590054"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,2]]},"references-count":6,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2017,2,2]]},"published-print":{"date-parts":[[2017,4]]}},"alternative-id":["10.1142\/S0218001417590054"],"URL":"https:\/\/doi.org\/10.1142\/s0218001417590054","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,2]]}}}