Theoretical Computer Science

s for Invited Talks Combinatorial Online Learning

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[2]  Xuelong Li,et al.  Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Lior Rokach,et al.  Survey on Collaborative Filtering, Content-based Filtering and Hybrid Recommendation System , 2015 .

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[12]  Tat-Seng Chua,et al.  Learning Image and User Features for Recommendation in Social Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[13]  Vito Latora,et al.  Measuring and modelling correlations in multiplex networks , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Yu Wei,et al.  Linking and Mapping of Library Catalogue Data Based on MapReduce , 2013 .

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[16]  V. N. Zadorozhnyi,et al.  Growing network: Models following nonlinear preferential attachment rule , 2015 .

[17]  Shuang-Hong Yang,et al.  Functional matrix factorizations for cold-start recommendation , 2011, SIGIR.

[18]  Mason A. Porter,et al.  Multilayer networks , 2013, J. Complex Networks.

[19]  Silvia Uribe,et al.  Social and Content Hybrid Image Recommender System for Mobile Social Networks , 2012, Mobile Networks and Applications.

[20]  Hongwu Ye,et al.  A Personalized Collaborative Filtering Recommendation Using Association Rules Mining and Self-Organizing Map , 2011, J. Softw..

[21]  Daniel L. Rubin,et al.  A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations , 2014, J. Biomed. Informatics.

[22]  Yamir Moreno,et al.  Lévy random walks on multiplex networks , 2016, Scientific Reports.

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[24]  George Lekakos,et al.  A hybrid approach for movie recommendation , 2006, Multimedia Tools and Applications.

[25]  Ginestra Bianconi,et al.  Percolation in multiplex networks with overlap. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[27]  Fei-Fei Li,et al.  Hierarchical semantic indexing for large scale image retrieval , 2011, CVPR 2011.

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[29]  K. A. D. N. K. Wimalawarne,et al.  picSEEK: Collaborative filtering for context-based image recommendation , 2010, 2010 Fifth International Conference on Information and Automation for Sustainability.

[30]  Wu Lei,et al.  Improved Personalized Recommendation based on Causal Association Rule and Collaborative Filtering , 2016, Int. J. Distance Educ. Technol..

[31]  Conrado J. Pérez Vicente,et al.  Diffusion dynamics on multiplex networks , 2012, Physical review letters.

[32]  S. N. Dorogovtsev,et al.  Multiple percolation transitions in a configuration model of a network of networks. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

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[34]  Marc Boullé,et al.  Comparing State-of-the-Art Collaborative Filtering Systems , 2007, MLDM.

[35]  Daniel L. Rubin,et al.  On combining image-based and ontological semantic dissimilarities for medical image retrieval applications , 2014, Medical Image Anal..

[36]  Sergio Gómez,et al.  On the dynamical interplay between awareness and epidemic spreading in multiplex networks , 2013, Physical review letters.

[37]  Minchao Ye,et al.  Preference transfer model in collaborative filtering for implicit data , 2016, Frontiers of Information Technology & Electronic Engineering.

[38]  Liana Stanescu,et al.  Automatic image annotation and semantic based image retrieval for medical domain , 2013, Neurocomputing.

[39]  J. J. Rocchio,et al.  Relevance feedback in information retrieval , 1971 .

[40]  Chi Huang,et al.  A microblog recommendation algorithm based on social tagging and a temporal interest evolution model , 2015, Frontiers of Information Technology & Electronic Engineering.

[41]  Vito Latora,et al.  Remote synchronization reveals network symmetries and functional modules. , 2012, Physical review letters.

[42]  Dong Liu,et al.  Comparative Deep Learning of Hybrid Representations for Image Recommendations , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[43]  Fernandez Lopez,et al.  Overview Of Methodologies For Building Ontologies , 1999, IJCAI 1999.

[44]  Kriengkrai Porkaew,et al.  Query refinement for multimedia similarity retrieval in MARS , 1999, MULTIMEDIA '99.

[45]  Thomas S. Huang,et al.  A novel relevance feedback technique in image retrieval , 1999, MULTIMEDIA '99.

[46]  Ah-Hwee Tan,et al.  Learning and inferencing in user ontology for personalized Semantic Web search , 2009, Inf. Sci..

[47]  Chunfeng Yang,et al.  Social-group-based ranking algorithms for cold-start video recommendation , 2016, International Journal of Data Science and Analytics.

[48]  Iván Cantador,et al.  Alleviating the new user problem in collaborative filtering by exploiting personality information , 2016, User Modeling and User-Adapted Interaction.

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[50]  V. R. Benjamins,et al.  Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem-Solving Methods , 1999, IJCAI 1999.

[51]  Vito Latora,et al.  Biased random walks on multiplex networks , 2015, ArXiv.

[52]  C. Buono,et al.  Epidemics in Partially Overlapped Multiplex Networks , 2013, PloS one.

[53]  Ouen Pinngern,et al.  A Combination of Content-based Filtering and Item-based Collaborative Filtering Using Association Rules , 2004 .

[54]  Nan Du,et al.  Improved recommendation based on collaborative tagging behaviors , 2008, IUI '08.

[55]  Dawei Zhao,et al.  Multiple routes transmitted epidemics on multiplex networks , 2013, ArXiv.