D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 34 Citations 13,627 78 World Ranking 6151 National Ranking 2966

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • The Internet

Matthew Richardson mainly investigates Information retrieval, Artificial intelligence, World Wide Web, Natural language processing and Ranking. In his study, Object, Access time, Quality, Backlink and HITS algorithm is strongly linked to Data mining, which falls under the umbrella field of Information retrieval. His research in Artificial intelligence intersects with topics in Markov chain and Statistical relational learning.

His study in the field of Semantic Web, The Internet and Social computing also crosses realms of Credibility and Web of trust. When carried out as part of a general Natural language processing research project, his work on Parsing is frequently linked to work in Multiple choice, Comprehension, Textual entailment and Grammar, therefore connecting diverse disciplines of study. The Search engine study combines topics in areas such as Ranking, Relevance and PageRank.

His most cited work include:

  • Markov logic networks (2324 citations)
  • Mining the network value of customers (2238 citations)
  • Mining knowledge-sharing sites for viral marketing (1385 citations)

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

His primary scientific interests are in Artificial intelligence, Information retrieval, World Wide Web, Machine learning and Search engine. His Artificial intelligence research is multidisciplinary, relying on both Pattern recognition, Markov chain and Natural language processing. His Markov chain study also includes

  • Inference that intertwine with fields like Statistical relational learning,
  • Theoretical computer science that intertwine with fields like Probabilistic logic.

His work on Parsing as part of general Natural language processing research is frequently linked to Comprehension, bridging the gap between disciplines. His Information retrieval study combines topics in areas such as Web page and Data mining. His study in the field of The Internet and Personalization is also linked to topics like Face and Web of trust.

He most often published in these fields:

  • Artificial intelligence (30.84%)
  • Information retrieval (29.91%)
  • World Wide Web (19.63%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (30.84%)
  • Severe acute respiratory syndrome coronavirus 2 (5.61%)
  • Natural language processing (8.41%)

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

Matthew Richardson focuses on Artificial intelligence, Severe acute respiratory syndrome coronavirus 2, Natural language processing, Parsing and Natural language. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition. His Parsing research is multidisciplinary, incorporating elements of Question answering, Knowledge base question answering, Value and Point.

His Knowledge base question answering study necessitates a more in-depth grasp of Information retrieval. Matthew Richardson performs integrative study on Information retrieval and Screen sharing in his works. Matthew Richardson has included themes like SQL and Code in his Natural language study.

Between 2014 and 2021, his most popular works were:

  • DyNet: The Dynamic Neural Network Toolkit (337 citations)
  • The Value of Semantic Parse Labeling for Knowledge Base Question Answering (163 citations)
  • Cryptic transmission of SARS-CoV-2 in Washington state. (109 citations)

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

  • Artificial intelligence
  • Machine learning
  • The Internet

Matthew Richardson spends much of his time researching Artificial intelligence, Natural language processing, Parsing, Pandemic and Transmission. His research on Artificial intelligence often connects related topics like Machine learning. His Natural language processing research includes themes of Correctness and Relation.

Within one scientific family, Matthew Richardson focuses on topics pertaining to Value under Parsing, and may sometimes address concerns connected to Information retrieval. His Information retrieval study frequently links to other fields, such as Point. The various areas that Matthew Richardson examines in his Transmission study include Epidemiology and Outbreak.

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

Markov logic networks

Matthew Richardson;Pedro Domingos.
Machine Learning (2006)

3103 Citations

Mining the network value of customers

Pedro Domingos;Matt Richardson.
knowledge discovery and data mining (2001)

2818 Citations

Mining knowledge-sharing sites for viral marketing

Matthew Richardson;Pedro Domingos.
knowledge discovery and data mining (2002)

1839 Citations

Trust management for the semantic web

Matthew Richardson;Rakesh Agrawal;Pedro Domingos.
international semantic web conference (2003)

1108 Citations

Predicting clicks: estimating the click-through rate for new ads

Matthew Richardson;Ewa Dominowska;Robert Ragno.
the web conference (2007)

998 Citations

The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank

Matthew Richardson;Pedro Domingos.
neural information processing systems (2001)

597 Citations

MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text

Matthew Richardson;Christopher J.C. Burges;Erin Renshaw.
empirical methods in natural language processing (2013)

529 Citations

DyNet: The Dynamic Neural Network Toolkit

Graham Neubig;Chris Dyer;Yoav Goldberg;Austin Matthews.
arXiv: Machine Learning (2017)

511 Citations

Yes, there is a correlation: - from social networks to personal behavior on the web

Parag Singla;Matthew Richardson.
the web conference (2008)

387 Citations

Dynamic client interaction for search

Matthew R. Richardson;Robert J. Ragno.
(2013)

350 Citations

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