2009 - ACM Senior Member
His primary areas of study are Information retrieval, Artificial intelligence, Data mining, World Wide Web and Search engine. His study brings together the fields of Web page and Information retrieval. His studies deal with areas such as Machine learning, Pattern recognition and Natural language processing as well as Artificial intelligence.
His Data mining research incorporates elements of Structure, Web application, Similarity and Link analysis. His World Wide Web study integrates concerns from other disciplines, such as Multimedia, Advertising and Ranking. The Search engine study combines topics in areas such as Online advertising and Market segmentation.
Information retrieval, Artificial intelligence, Data mining, Web page and World Wide Web are his primary areas of study. Information retrieval is represented through his Web search query, Search engine, Web query classification, Query expansion and Ranking research. The concepts of his Search engine study are interwoven with issues in Online advertising and Relevance.
His Artificial intelligence research integrates issues from Natural language processing, Machine learning and Pattern recognition. Zheng Chen has included themes like Set, Cluster analysis, Link analysis, Algorithm and Feature selection in his Data mining study. His research integrates issues of Context, Multimedia and Advertising in his study of World Wide Web.
Zheng Chen mainly investigates Information retrieval, Artificial intelligence, Search engine, Machine learning and Data mining. His Information retrieval research includes elements of Web page and Knowledge base. Many of his studies involve connections with topics such as Natural language processing and Artificial intelligence.
His biological study spans a wide range of topics, including Multi-objective optimization, The Internet, Relevance and Click-through rate. His Machine learning study incorporates themes from Matrix decomposition, Data set, Relation and Task. His Data mining research is multidisciplinary, incorporating perspectives in Collaborative filtering, MovieLens, Human–computer interaction, Cluster analysis and Implementation.
Artificial intelligence, Information retrieval, Natural language processing, Machine learning and Embedding are his primary areas of study. Artificial intelligence and Computer vision are commonly linked in his work. Information retrieval and Focus are frequently intertwined in his study.
His Natural language processing research is multidisciplinary, incorporating elements of Space, Word-sense disambiguation, Training set and Knowledge base. The various areas that Zheng Chen examines in his Machine learning study include Reduction, Named-entity recognition, Data mining and Categorization. Zheng Chen interconnects WordNet and Entity linking in the investigation of issues within Embedding.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Knowledge graph embedding by translating on hyperplanes
Zhen Wang;Jianwen Zhang;Jianlin Feng;Zheng Chen.
national conference on artificial intelligence (2014)
Scalable collaborative filtering using cluster-based smoothing
Gui-Rong Xue;Chenxi Lin;Qiang Yang;WenSi Xi.
international acm sigir conference on research and development in information retrieval (2005)
Learning to cluster web search results
Hua-Jun Zeng;Qi-Cai He;Zheng Chen;Wei-Ying Ma.
international acm sigir conference on research and development in information retrieval (2004)
Cross-domain sentiment classification via spectral feature alignment
Sinno Jialin Pan;Xiaochuan Ni;Jian-Tao Sun;Qiang Yang.
the web conference (2010)
CubeSVD: a novel approach to personalized Web search
Jian-Tao Sun;Hua-Jun Zeng;Huan Liu;Yuchang Lu.
the web conference (2005)
How much can behavioral targeting help online advertising
Jun Yan;Ning Liu;Gang Wang;Wen Zhang.
the web conference (2009)
An evaluation on feature selection for text clustering
Tao Liu;Shengping Liu;Zheng Chen;Wei-Ying Ma.
international conference on machine learning (2003)
Document summarization using conditional random fields
Dou Shen;Jian-Tao Sun;Hua Li;Qiang Yang.
international joint conference on artificial intelligence (2007)
Media agent to suggest contextually related media content
Wen-Yin Liu;Hong-Jiang Zhang;Zheng Chen.
(2001)
Optimizing web search using web click-through data
Gui-Rong Xue;Hua-Jun Zeng;Zheng Chen;Yong Yu.
conference on information and knowledge management (2004)
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