Seamlessly Integrating Effective Links with Attributes for Networked Data Classification
Zhao,Yangyang; Sun,Zhengya; Xu,Changsheng; Hao,Hongwei
2015-05
会议名称The 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
会议录名称Advances in Knowledge Discovery and Data Mining
会议日期May 19, 2015 - May 22, 2015
会议地点Ho Chi Minh City, Vietnam
摘要
Networked data is emerging with great amount in various fields like social networks, biological networks, research publication networks, etc. Networked data classification is therefore of critical importance in real world, and it is noticed that link information can help
improve learning performance. However, classification of such networked data can be challenging since: 1) the original links (also referred as relations) in such networks, are always sparse, incomplete and noisy; 2) it is not easy to characterize, select and leverage effective link information from the networks, involving multiple types of links with distinct
semantics; 3) it is difficult to seamlessly integrate link information with attribute information in a network. To address these limitations, in this paper we develop a novel Seamlessly-integrated Link-Attribute Collective Matrix Factorization (SLA-CMF) framework, which mines highly effective link information given arbitrary information network and leverages
it with attribute information in a unified perspective. Algorithmwise, SLA-CMF first mines highly effective link information via link path weighting and link strength learning. Then it learns a low-dimension linkattribute joint representation via graph Laplacian CMF. Finally the joint representation is put into a traditional classifier such as SVM for classification.
Extensive experiments on benchmark datasets demonstrate the effectiveness of our method.
关键词Networked Data Classification Heterogeneous Information Fusion Collective Matrix Factorization
收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11951
专题模式识别国家重点实验室_多媒体计算与图形学
通讯作者Sun,Zhengya
作者单位Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Zhao,Yangyang,Sun,Zhengya,Xu,Changsheng,et al. Seamlessly Integrating Effective Links with Attributes for Networked Data Classification[C],2015.
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