His primary scientific interests are in Artificial intelligence, Information retrieval, Natural language processing, Query expansion and Language model. His work deals with themes such as Carry, Context and Machine learning, which intersect with Artificial intelligence. Jian-Yun Nie specializes in Information retrieval, namely Ranking.
His study in Natural language processing is interdisciplinary in nature, drawing from both Word and Translation. His study focuses on the intersection of Query expansion and fields such as Query language with connections in the field of Query optimization. In his study, Sentence, Supervised learning, Support vector machine and Unsupervised learning is inextricably linked to Term, which falls within the broad field of Language model.
His scientific interests lie mostly in Information retrieval, Artificial intelligence, Natural language processing, Query expansion and Language model. His research on Information retrieval often connects related topics like Ranking. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Pattern recognition.
His Natural language processing research is multidisciplinary, relying on both Context and Translation. His Query expansion study combines topics in areas such as Query language, Data mining, Query optimization, RDF query language and Term. His biological study spans a wide range of topics, including Spatial query and Concept search.
Jian-Yun Nie focuses on Artificial intelligence, Natural language processing, Information retrieval, Artificial neural network and Machine learning. In the field of Artificial intelligence, his study on Sentence and Ranking overlaps with subjects such as Empirical research and Process. His research integrates issues of Document retrieval, Query expansion, Deep learning and Hyperparameter optimization in his study of Ranking.
Jian-Yun Nie has researched Natural language processing in several fields, including SemEval and Emotion classification. He frequently studies issues relating to Context and Information retrieval. His work in the fields of Labeled data overlaps with other areas such as Sampling.
His primary areas of investigation include Artificial intelligence, Ranking, Artificial neural network, Natural language processing and Ranking. Artificial intelligence is closely attributed to Machine learning in his work. His Ranking research incorporates themes from Information retrieval, Search engine, Human–computer interaction and User profile.
In his work, Jian-Yun Nie performs multidisciplinary research in Information retrieval and Set. His Natural language processing research is multidisciplinary, incorporating perspectives in Decoding methods and Salience. The various areas that Jian-Yun Nie examines in his Ranking study include Document retrieval, Query expansion, Deep learning and Hyperparameter optimization.
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A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
Alessandro Sordoni;Michel Galley;Michael Auli;Chris Brockett.
north american chapter of the association for computational linguistics (2015)
Clustering user queries of a search engine
Ji-Rong Wen;Jian-Yun Nie;Hong-Jiang Zhang.
the web conference (2001)
Probabilistic query expansion using query logs
Hang Cui;Ji-Rong Wen;Jian-Yun Nie;Wei-Ying Ma.
the web conference (2002)
Query Clustering Using User Logs
Ji-Rong Wen;Jian-Yun Nie;HongJiang Zhang.
ACM Transactions on Information Systems (2002)
Selecting good expansion terms for pseudo-relevance feedback
Guihong Cao;Jian-Yun Nie;Jianfeng Gao;Stephen Robertson.
international acm sigir conference on research and development in information retrieval (2008)
Cross-language information retrieval based on parallel texts and automatic mining of parallel texts from the Web
Jian-Yun Nie;Michel Simard;Pierre Isabelle;Richard Durand.
international acm sigir conference on research and development in information retrieval (1999)
Query expansion by mining user logs
Hang Cui;Ji-Rong Wen;Jian-Yun Nie;Wei-Ying Ma.
IEEE Transactions on Knowledge and Data Engineering (2003)
A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion
Alessandro Sordoni;Yoshua Bengio;Hossein Vahabi;Christina Lioma.
conference on information and knowledge management (2015)
Dependence language model for information retrieval
Jianfeng Gao;Jian-Yun Nie;Guangyuan Wu;Guihong Cao.
international acm sigir conference on research and development in information retrieval (2004)
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun;Zhi-Hong Deng;Jian-Yun Nie;Jian Tang.
international conference on learning representations (2018)
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