{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T19:51:03Z","timestamp":1779306663056,"version":"3.51.4"},"reference-count":8,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Science and Technology Project","award":["2015BAH09F02"],"award-info":[{"award-number":["2015BAH09F02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>Clustering algorithm as a basis of data analysis is widely used in analysis systems. However, as for the high dimensions of the data, the clustering algorithm may overlook the business relation between these dimensions especially in the medical fields. As a result, usually the clustering result may not meet the business goals of the users. Then, in the clustering process, if it can combine the knowledge of the users, that is, the doctor\u2019s knowledge or the analysis intent, the clustering result can be more satisfied. In this paper, we propose an interactive <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>K<\/mml:mi><\/mml:mrow><\/mml:math>-means clustering method to improve the user\u2019s satisfactions towards the result. The core of this method is to get the user\u2019s feedback of the clustering result, to optimize the clustering result. Then, a particle swarm optimization algorithm is used in the method to optimize the parameters, especially the weight settings in the clustering algorithm to make it reflect the user\u2019s business preference as possible. After that, based on the parameter optimization and adjustment, the clustering result can be closer to the user\u2019s requirement. Finally, we take an example in the breast cancer, to testify our method. The experiments show the better performance of our algorithm.<\/jats:p>","DOI":"10.1155\/2017\/4915828","type":"journal-article","created":{"date-parts":[[2017,10,26]],"date-time":"2017-10-26T19:31:07Z","timestamp":1509046267000},"page":"1-9","source":"Crossref","is-referenced-by-count":10,"title":["Interactive <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>K<\/mml:mi><\/mml:mrow><\/mml:math>-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine"],"prefix":"10.1155","volume":"2017","author":[{"given":"Yang","family":"Lei","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3534-0745","authenticated-orcid":true,"given":"Dai","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Software, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Bin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2013.224"},{"issue":"9","key":"3","first-page":"2365","volume":"36","year":"2015","journal-title":"Computer Engineering and Design"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.109"},{"key":"6","first-page":"1","volume-title":"Clustering methods in data mining: a survey","year":"2001"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.22"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1145\/331499.331504"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1017616"},{"issue":"12","key":"11","first-page":"2796","volume":"37","year":"2015","journal-title":"Journal of Electronics and Information Technology"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/4915828.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/4915828.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2017\/4915828.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,10,26]],"date-time":"2017-10-26T19:31:09Z","timestamp":1509046269000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cmmm\/2017\/4915828\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":8,"alternative-id":["4915828","4915828"],"URL":"https:\/\/doi.org\/10.1155\/2017\/4915828","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"value":"1748-670X","type":"print"},{"value":"1748-6718","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}