H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 39 Citations 6,211 146 World Ranking 4818 National Ranking 2387

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His scientific interests lie mostly in Information retrieval, Relevance, Artificial intelligence, Machine learning and Semantic search. His research integrates issues of Session and Web page in his study of Information retrieval. The Relevance study combines topics in areas such as User interface design, World Wide Web, Preference and Interaction design.

His work focuses on many connections between Artificial intelligence and other disciplines, such as Natural language processing, that overlap with his field of interest in Redundancy. The concepts of his Machine learning study are interwoven with issues in Empirical research and Training set. His research investigates the link between Web search query and topics such as Ranking that cross with problems in Web query classification.

His most cited work include:

  • Guidelines for Human-AI Interaction (247 citations)
  • Modeling the impact of short- and long-term behavior on search personalization (216 citations)
  • Pairwise ranking aggregation in a crowdsourced setting (209 citations)

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

Information retrieval, Artificial intelligence, Machine learning, Data mining and Relevance are his primary areas of study. His Ranking, Search engine, Web search query, Web query classification and Semantic search investigations are all subjects of Information retrieval research. His Artificial intelligence research is multidisciplinary, relying on both Query expansion and Natural language processing.

Paul N. Bennett has researched Machine learning in several fields, including Sampling and Inference. The various areas that Paul N. Bennett examines in his Data mining study include Probabilistic logic and Classifier. His Relevance study incorporates themes from Learning to rank and Preference.

He most often published in these fields:

  • Information retrieval (37.72%)
  • Artificial intelligence (32.93%)
  • Machine learning (22.75%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (32.93%)
  • Information retrieval (37.72%)
  • Human–computer interaction (10.18%)

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

His primary areas of investigation include Artificial intelligence, Information retrieval, Human–computer interaction, Representation and Machine learning. His studies in Artificial intelligence integrate themes in fields like Ranking and Natural language processing. He is interested in Search engine, which is a branch of Information retrieval.

Paul N. Bennett focuses mostly in the field of Human–computer interaction, narrowing it down to matters related to Personalization and, in some cases, Variety. His Representation study also includes fields such as

  • Similarity, Paraphrase, Nearest neighbor search and Information seeking most often made with reference to Encoder,
  • Task that intertwine with fields like Data mining. His work on k-nearest neighbors algorithm and Leverage is typically connected to Bottleneck as part of general Machine learning study, connecting several disciplines of science.

Between 2018 and 2021, his most popular works were:

  • Guidelines for Human-AI Interaction (247 citations)
  • Will You Accept an Imperfect AI?: Exploring Designs for Adjusting End-user Expectations of AI Systems (51 citations)
  • Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval (48 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Paul N. Bennett spends much of his time researching Human–computer interaction, Artificial intelligence, Focus, Set and Information retrieval. His Human–computer interaction research is multidisciplinary, incorporating elements of Ai systems, End user and Key. His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Machine learning.

His research in Machine learning intersects with topics in Sampling, Importance sampling, Convergence and Word. Within one scientific family, Paul N. Bennett focuses on topics pertaining to Nearest neighbor search under Information retrieval, and may sometimes address concerns connected to Representation. As a part of the same scientific study, Paul N. Bennett usually deals with the Interaction design, concentrating on Relevance and frequently concerns with Test.

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

Guidelines for Human-AI Interaction

Saleema Amershi;Dan Weld;Mihaela Vorvoreanu;Adam Fourney.
human factors in computing systems (2019)

316 Citations

Pairwise ranking aggregation in a crowdsourced setting

Xi Chen;Paul N. Bennett;Kevyn Collins-Thompson;Eric Horvitz.
web search and data mining (2013)

312 Citations

Modeling the impact of short- and long-term behavior on search personalization

Paul N. Bennett;Ryen W. White;Wei Chu;Susan T. Dumais.
international acm sigir conference on research and development in information retrieval (2012)

283 Citations

Here or There

Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais.
european conference on information retrieval (2008)

232 Citations

Dual Strategy Active Learning

Pinar Donmez;Jaime G. Carbonell;Paul N. Bennett.
european conference on machine learning (2007)

205 Citations

Predicting short-term interests using activity-based search context

Ryen W. White;Paul N. Bennett;Susan T. Dumais.
conference on information and knowledge management (2010)

192 Citations

Personalizing web search results by reading level

Kevyn Collins-Thompson;Paul N. Bennett;Ryen W. White;Sebastian de la Chica.
conference on information and knowledge management (2011)

188 Citations

Modeling and analysis of cross-session search tasks

Alexander Kotov;Paul N. Bennett;Ryen W. White;Susan T. Dumais.
international acm sigir conference on research and development in information retrieval (2011)

171 Citations

Here or there: preference judgments for relevance

Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais.
Proceedings of the IR research, 30th European conference on Advances in information retrieval (2008)

157 Citations

Refined experts: improving classification in large taxonomies

Paul N. Bennett;Nam Nguyen.
international acm sigir conference on research and development in information retrieval (2009)

152 Citations

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