کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6940071 | 869737 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Ensemble clustering using factor graph
ترجمه فارسی عنوان
خوشه بندی گروهی با استفاده از گراف عامل
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کلمات کلیدی
گروه خوشه بندی نمودار فاکتور، انتشار اعتقاد، سوپر شی، برآورد تعداد خوشه خودکار،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In this paper, we propose a new ensemble clustering approach termed ensemble clustering using factor graph (ECFG). Compared to the existing approaches, our approach has three main advantages: (1) the cluster number is obtained automatically and need not to be specified in advance; (2) the reliability of each base clustering can be estimated in an unsupervised manner and exploited in the consensus process; (3) our approach is efficient for processing ensembles with large data sizes and large ensemble sizes. In this paper, we introduce the concept of super-object, which serves as a compact and adaptive representation for the ensemble data and significantly facilitates the computation. Through the probabilistic formulation, we cast the ensemble clustering problem into a binary linear programming (BLP) problem. The BLP problem is NP-hard. To solve this optimization problem, we propose an efficient solver based on factor graph. The constrained objective function is represented as a factor graph and the max-product belief propagation is utilized to generate the solution insensitive to initialization and converged to the neighborhood maximum. Extensive experiments are conducted on multiple real-world datasets, which demonstrate the effectiveness and efficiency of our approach against the state-of-the-art approaches.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 50, February 2016, Pages 131-142
Journal: Pattern Recognition - Volume 50, February 2016, Pages 131-142
نویسندگان
Dong Huang, Jianhuang Lai, Chang-Dong Wang,