{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,31]],"date-time":"2024-03-31T22:10:22Z","timestamp":1711923022686},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2168,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically.<\/jats:p><jats:p>Results: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix.<\/jats:p><jats:p>Availability: The MATLAB code of algorithms implemented in this paper is downloadable from http:\/\/homes.esat.kuleuven.be\/~sistawww\/bioi\/syu\/oklc.html.<\/jats:p><jats:p>Contact: \u00a0shiyu@uchicago.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq569","type":"journal-article","created":{"date-parts":[[2010,10,28]],"date-time":"2010-10-28T00:19:07Z","timestamp":1288225147000},"page":"118-126","source":"Crossref","is-referenced-by-count":16,"title":["Optimized data fusion for K-means Laplacian clustering"],"prefix":"10.1093","volume":"27","author":[{"given":"Shi","family":"Yu","sequence":"first","affiliation":[{"name":"1 Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium, 2Department of Information Science and Engineering & ERCMAMT, Wuhan University of Science and Technology, Wuhan, China and 3Department of Managerial Economics, Strategy and Innovation, Centre for R & D Monitoring, Katholieke Universiteit Leuven, Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinhai","family":"Liu","sequence":"additional","affiliation":[{"name":"1 Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium, 2Department of Information Science and Engineering & ERCMAMT, Wuhan University of Science and Technology, Wuhan, China and 3Department of Managerial Economics, Strategy and Innovation, Centre for R & D Monitoring, Katholieke Universiteit Leuven, Leuven, Belgium"},{"name":"1 Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium, 2Department of Information Science and Engineering & ERCMAMT, Wuhan University of Science and Technology, Wuhan, China and 3Department of Managerial Economics, Strategy and Innovation, Centre for R & D Monitoring, Katholieke Universiteit Leuven, Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L\u00e9on-Charles","family":"Tranchevent","sequence":"additional","affiliation":[{"name":"1 Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium, 2Department of Information Science and Engineering & ERCMAMT, Wuhan University of Science and Technology, Wuhan, China and 3Department of Managerial Economics, Strategy and Innovation, Centre for R & D Monitoring, Katholieke Universiteit Leuven, Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wolfgang","family":"Gl\u00e4nzel","sequence":"additional","affiliation":[{"name":"1 Signals, Identification, System Theory and Automation, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium, 2Department of Information Science and Engineering & ERCMAMT, Wuhan University of Science and Technology, Wuhan, China and 3Department of Managerial Economics, Strategy and Innovation, Centre for R & D Monitoring, Katholieke Universiteit Leuven, Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johan A. 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Decis."},{"key":"2023012511163061000_B6","first-page":"551","article-title":"Kernel k-means, spectral clustering and normalized cuts","volume-title":"Proceedings of the 10th ACM KDD.","author":"Dhillon","year":"2004"},{"key":"2023012511163061000_B7","first-page":"225","article-title":"K-means clustering via principal component analysis","volume-title":"21st International Conference on Machine Learning.","author":"Ding","year":"2004"},{"key":"2023012511163061000_B8","volume-title":"Pattern Classification","author":"Duda","year":"2001","edition":"2"},{"key":"2023012511163061000_B9","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1109\/TPAMI.2005.113","article-title":"Combining multiple clusterings using evidence accumulation","volume":"27","author":"Fred","year":"2005","journal-title":"IEEE Trans. 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