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Breast mass classification via deeply integrating the contextual information from multi-view data
Pattern Recognition, 2018Automatic differentiation of benign and malignant mammography images is a challenging task. Recently, Convolutional Neural Networks (CNNs) have been proposed to address this task based on raw pixel input.
Hongyu Wang +6 more
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MultiSpectralNet: Spectral Clustering Using Deep Neural Network for Multi-View Data
IEEE Transactions on Computational Social Systems, 2019Multi-view data provide more comprehensive information than single views by providing different feature sets of the same object. Learning its data structure through spectral clustering has always been the mainstream of research.
Shuning Huang +3 more
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SSDMV: Semi-Supervised Deep Social Spammer Detection by Multi-view Data Fusion
Industrial Conference on Data Mining, 2018The explosive use of social media makes it a popular platform for malicious users, known as social spammers, to overwhelm legitimate users with unwanted content.
Chaozhuo Li +5 more
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Co-training on multi-view unlabelled data
Proceedings of the 27th Conference on Image and Vision Computing New Zealand, 2012A novel co-training framework is proposed for object orientation estimation in a multi-camera network environment. The model is initialised using a small labelled dataset and then iteratively boosted using large amount of unlabelled data which are generated automatically from videos.
Michał Lewandowski, James Orwell
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Multi-view data clustering via non-negative matrix factorization with manifold regularization
International Journal of Machine Learning and Cybernetics, 2021G. Khan +4 more
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Multi-View Concept Learning for Data Representation
IEEE Transactions on Knowledge and Data Engineering, 2015Real-world datasets often involve multiple views of data items, e.g., a Web page can be described by both its content and anchor texts of hyperlinks leading to it; photos in Flickr could be characterized by visual features, as well as user contributed tags. Different views provide information complementary to each other.
Ziyu Guan +3 more
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Simple Contrastive Multi-View Clustering with Data-Level Fusion
International Joint Conference on Artificial IntelligencePrevious deep multi-view clustering methods usually design un-shared encoders to explore the cluster information among multi-view data, but they are difficult to customize the encoders for individual views and easily increase information loss. To address
Caixuan Luo +4 more
semanticscholar +1 more source
Sentiment Analysis on Multi-view Social Data
2016With the proliferation of social networks, people are likely to share their opinions about news, social events and products on the Web. There is an increasing interest in understanding users’ attitude or sentiment from the large repository of opinion-rich data on the Web. This can benefit many commercial and political applications.
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Modeling and Maintaining Multi-view Data Warehouses
1999Data warehouses are designed mostly as centralized systems, andt he majority of update maintenance algorithms are tailored for this specific model. Maintenance methods have been proposed either under the assumption of a single view data warehouse, a multi-view centralized model, or a multi-view distributed system with strict synchronization ...
I. Stanoi, D. Agrawal, A. El Abbadi
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Multi-view Semantic Learning for Data Representation
2015Many real-world datasets are represented by multiple features or modalities which often provide compatible and complementary information to each other. In order to obtain a good data representation that synthesizes multiple features, researchers have proposed different multi-view subspace learning algorithms.
Peng Luo +3 more
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