Multi-view Machines

With rapidly growing amount of data available on the web, it becomes increasingly likely to obtain data from different perspectives for multi-view learning. Some successive examples of web applications include recommendation and target advertising. Specifically, to predict whether a user will click an ad in a query context, there are available features extracted from user profile, ad information and query description, and each of them can only capture part of the task signals from a particular aspect/view. Different views provide complementary information to learn a practical model for these applications. Therefore, an effective integration of the multi-view information is critical to facilitate the learning performance. In this paper, we propose a general predictor, named multiview machines (MVMs), that can effectively explore the full-order interactions between features from multiple views. A joint factorization is applied for the interaction parameters which makes parameter e...

• Type: Journal
• Year: 2016
• Where: WSDM
• Authors: Bokai Cao, Hucheng Zhou, Guoqiang Li, Philip S. Yu
• Keywords: Data Mining, WSDM 2016