Minlie Huang mostly deals with Artificial intelligence, Natural language processing, Machine learning, Information retrieval and Conversation. In his research, Minlie Huang performs multidisciplinary study on Artificial intelligence and Protein–protein interaction. His study in Natural language processing is interdisciplinary in nature, drawing from both Annotation and Conjunction.
His work deals with themes such as Information extraction and Forum spam, Spambot, which intersect with Machine learning. Minlie Huang combines subjects such as Ranking, Context, World Wide Web and Biological database with his study of Information retrieval. His Conversation research includes themes of Commonsense knowledge and Vocabulary.
Minlie Huang mainly focuses on Artificial intelligence, Natural language processing, Machine learning, Human–computer interaction and Dialog box. Artificial intelligence is closely attributed to Context in his research. His Natural language processing research incorporates themes from Commonsense knowledge and Comprehension.
His work carried out in the field of Machine learning brings together such families of science as Text mining, Generative model and Robustness. The Human–computer interaction study combines topics in areas such as Semantics, Conversation, State and Reinforcement learning. His Dialog box research is multidisciplinary, relying on both Task oriented and Component.
His primary areas of study are Artificial intelligence, Dialog box, Human–computer interaction, Natural language processing and Conversation. Artificial intelligence and Machine learning are frequently intertwined in his study. His work in the fields of Leverage overlaps with other areas such as Beam search.
His Dialog system study in the realm of Dialog box connects with subjects such as Multi domain. His studies deal with areas such as Variety, Component and Reinforcement learning as well as Human–computer interaction. His work deals with themes such as Context, Self training and Knowledge graph, which intersect with Natural language processing.
The scientist’s investigation covers issues in Dialog box, Artificial intelligence, Natural language processing, Human–computer interaction and Dialog system. He has included themes like Domain, Semantics, Conversation and Component in his Dialog box study. His study in Repetition extends to Artificial intelligence with its themes.
His study in the field of Question answering also crosses realms of Base. His research in Human–computer interaction intersects with topics in Natural language, Decomposition, Domain knowledge and Reinforcement learning. The Dialog system study combines topics in areas such as Interpersonal communication and Task oriented.
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.
Attention-based LSTM for Aspect-level Sentiment Classification
Yequan Wang;Minlie Huang;xiaoyan zhu;Li Zhao.
empirical methods in natural language processing (2016)
Learning to identify review spam
Fangtao Li;Minlie Huang;Yi Yang;Xiaoyan Zhu.
international joint conference on artificial intelligence (2011)
Structure-Aware Review Mining and Summarization
Fangtao Li;Chao Han;Minlie Huang;Xiaoyan Zhu.
international conference on computational linguistics (2010)
Discovering patterns to extract protein--protein interactions from full texts
Minlie Huang;Xiaoyan Zhu;Yu Hao;Donald G. Payan.
Sentiment analysis with global topics and local dependency
Fangtao Li;Minlie Huang;Xiaoyan Zhu.
national conference on artificial intelligence (2010)
TransG : A Generative Model for Knowledge Graph Embedding
Han Xiao;Minlie Huang;Xiaoyan Zhu.
meeting of the association for computational linguistics (2016)
Commonsense Knowledge Aware Conversation Generation with Graph Attention
Hao Zhou;Tom Young;Minlie Huang;Haizhou Zhao.
international joint conference on artificial intelligence (2018)
Augmenting end-to-end dialogue systems with commonsense knowledge
Tom Young;Erik Cambria;Iti Chaturvedi;Hao Zhou.
national conference on artificial intelligence (2018)
The gene normalization task in BioCreative III
Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang.
BMC Bioinformatics (2011)
Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory.
Hao Zhou;Minlie Huang;Tianyang Zhang;Xiaoyan Zhu.
national conference on artificial intelligence (2017)
Profile was last updated on December 6th, 2021.
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The ranking h-index is inferred from publications deemed to belong to the considered discipline.
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