What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Information retrieval
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 most cited work include:
- A Neural Network Approach to Context-Sensitive Generation of Conversational Responses (587 citations)
- Query Clustering Using User Logs (440 citations)
- Clustering user queries of a search engine (439 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Information retrieval (51.33%)
- Artificial intelligence (47.53%)
- Natural language processing (31.94%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (47.53%)
- Natural language processing (31.94%)
- Information retrieval (51.33%)
In recent papers he was focusing on the following fields of study:
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.
Between 2017 and 2021, his most popular works were:
- RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space (282 citations)
- RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space (54 citations)
- An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems. (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Information retrieval
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.
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.
