H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 40 Citations 7,263 155 World Ranking 4587 National Ranking 430

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Matching, Natural language processing and Relevance. His work in Artificial intelligence addresses issues such as Ranking, which are connected to fields such as Ranking. His Machine learning research incorporates elements of Language model and Representation.

His Matching research integrates issues from Question answering and Pattern recognition. The various areas that Jiafeng Guo examines in his Natural language processing study include Context and Task. In his study, Identification and Heuristics is strongly linked to Benchmark, which falls under the umbrella field of Relevance.

His most cited work include:

  • A biterm topic model for short texts (557 citations)
  • A Deep Relevance Matching Model for Ad-hoc Retrieval (511 citations)
  • Named entity recognition in query (336 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Artificial intelligence, Information retrieval, Machine learning, Ranking and Ranking. His Artificial intelligence study incorporates themes from Matching, Relevance and Natural language processing. He interconnects Web page, Deep learning and Information needs in the investigation of issues within Information retrieval.

His work on Stochastic gradient descent and Recurrent neural network as part of general Machine learning research is frequently linked to Process and Markov decision process, thereby connecting diverse disciplines of science. His Ranking research is multidisciplinary, relying on both Vocabulary mismatch, Data mining and Pairwise comparison. His Ranking study integrates concerns from other disciplines, such as Artificial neural network and Automatic summarization.

He most often published in these fields:

  • Artificial intelligence (58.26%)
  • Information retrieval (29.82%)
  • Machine learning (27.98%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (58.26%)
  • Information retrieval (29.82%)
  • Natural language processing (19.72%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Information retrieval, Natural language processing, Benchmark and Question answering. His Artificial intelligence study frequently draws connections between adjacent fields such as Pattern recognition. His Information retrieval research includes themes of Ranking and Natural language.

His work on Language model as part of general Natural language processing research is frequently linked to Process, Generator and Causal reasoning, bridging the gap between disciplines. Jiafeng Guo combines subjects such as Variety and Machine learning, Feature learning with his study of Benchmark. His biological study spans a wide range of topics, including Artificial neural network and Vocabulary mismatch.

Between 2019 and 2021, his most popular works were:

  • A Deep Look into neural ranking models for information retrieval (51 citations)
  • IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems (9 citations)
  • NeuInfer: Knowledge Inference on N-ary Facts (6 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Jiafeng Guo mainly investigates Artificial intelligence, Natural language processing, Benchmark, Transformer and Utterance. His research brings together the fields of Context and Artificial intelligence. His Language model study in the realm of Natural language processing connects with subjects such as Document Structure Description.

His Benchmark research includes elements of Machine learning and Feature learning. His work deals with themes such as Sampling and Vocabulary mismatch, which intersect with Machine learning. His study looks at the relationship between Transformer and fields such as Ranking, as well as how they intersect with chemical problems.

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.

Best Publications

A biterm topic model for short texts

Xiaohui Yan;Jiafeng Guo;Yanyan Lan;Xueqi Cheng.
the web conference (2013)

824 Citations

A Deep Relevance Matching Model for Ad-hoc Retrieval

Jiafeng Guo;Yixing Fan;Qingyao Ai;W. Bruce Croft.
conference on information and knowledge management (2016)

428 Citations

Named entity recognition in query

Jiafeng Guo;Gu Xu;Xueqi Cheng;Hang Li.
international acm sigir conference on research and development in information retrieval (2009)

390 Citations

BTM: Topic Modeling over Short Texts

Xueqi Cheng;Xiaohui Yan;Yanyan Lan;Jiafeng Guo.
IEEE Transactions on Knowledge and Data Engineering (2014)

387 Citations

Learning Hierarchical Representation Model for NextBasket Recommendation

Pengfei Wang;Jiafeng Guo;Yanyan Lan;Jun Xu.
international acm sigir conference on research and development in information retrieval (2015)

256 Citations

A deep architecture for semantic matching with multiple positional sentence representations

Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu.
national conference on artificial intelligence (2016)

189 Citations

Text Matching as Image Recognition

Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu.
arXiv: Computation and Language (2016)

174 Citations

A unified and discriminative model for query refinement

Jiafeng Guo;Gu Xu;Hang Li;Xueqi Cheng.
international acm sigir conference on research and development in information retrieval (2008)

158 Citations

Quantifying and identifying the overlapping community structure in networks

Hua-Wei Shen;Xue-Qi Cheng;Jia-Feng Guo.
Journal of Statistical Mechanics: Theory and Experiment (2009)

153 Citations

aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model

Liu Yang;Qingyao Ai;Jiafeng Guo;W. Bruce Croft.
conference on information and knowledge management (2016)

149 Citations

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Best Scientists Citing Jiafeng Guo

W. Bruce Croft

W. Bruce Croft

University of Massachusetts Amherst

Publications: 80

Maarten de Rijke

Maarten de Rijke

University of Amsterdam

Publications: 63

Xueqi Cheng

Xueqi Cheng

Chinese Academy of Sciences

Publications: 39

Ji-Rong Wen

Ji-Rong Wen

Renmin University of China

Publications: 28

Yongfeng Zhang

Yongfeng Zhang

Rutgers, The State University of New Jersey

Publications: 26

Nick Craswell

Nick Craswell

Microsoft (United States)

Publications: 20

Jamie Callan

Jamie Callan

Carnegie Mellon University

Publications: 20

Jimmy Lin

Jimmy Lin

University of Waterloo

Publications: 20

Krisztian Balog

Krisztian Balog

University of Stavanger

Publications: 20

Marc Najork

Marc Najork

Google (United States)

Publications: 20

Xindong Wu

Xindong Wu

Hefei University of Technology

Publications: 19

Jian-Yun Nie

Jian-Yun Nie

University of Montreal

Publications: 18

Xuanhui Wang

Xuanhui Wang

Google (United States)

Publications: 18

Ophir Frieder

Ophir Frieder

Georgetown University

Publications: 17

Xiangnan He

Xiangnan He

University of Science and Technology of China

Publications: 17

Donald Metzler

Donald Metzler

Google (United States)

Publications: 17

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