H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 50 Citations 8,461 255 World Ranking 2910 National Ranking 1537

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Information retrieval
  • Machine learning

Douglas W. Oard mainly investigates Information retrieval, Artificial intelligence, Natural language processing, Relevance and Human–computer information retrieval. In his works, Douglas W. Oard undertakes multidisciplinary study on Information retrieval and Term. His Artificial intelligence research focuses on Clef and how it connects with Fuzzy logic.

His Natural language processing research is mostly focused on the topic Cross-language information retrieval. As part of one scientific family, Douglas W. Oard deals mainly with the area of Relevance, narrowing it down to issues related to the Test, and often Variety, Formative assessment and Ranking. His research integrates issues of Document retrieval and Concept search in his study of Human–computer information retrieval.

His most cited work include:

  • Implicit Feedback for Recommender Systems (319 citations)
  • Cross-Language Information Retrieval. (249 citations)
  • A survey of information retrieval and filtering methods (215 citations)

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

The scientist’s investigation covers issues in Information retrieval, Artificial intelligence, Natural language processing, World Wide Web and Relevance. His Information retrieval research incorporates elements of Test and Clef. As a part of the same scientific family, Douglas W. Oard mostly works in the field of Artificial intelligence, focusing on Query expansion and, on occasion, Query language.

The various areas that Douglas W. Oard examines in his Natural language processing study include Translation, Arabic, Search engine indexing and Multilingualism. His Machine translation research integrates issues from Information access, Context and Rule-based machine translation. His work deals with themes such as Document retrieval and Concept search, which intersect with Human–computer information retrieval.

He most often published in these fields:

  • Information retrieval (45.15%)
  • Artificial intelligence (40.61%)
  • Natural language processing (35.15%)

What were the highlights of his more recent work (between 2015-2021)?

  • Information retrieval (45.15%)
  • Artificial intelligence (40.61%)
  • Test (8.79%)

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

Douglas W. Oard focuses on Information retrieval, Artificial intelligence, Test, Natural language processing and Clef. His Information retrieval research is multidisciplinary, incorporating elements of Annotation and Machine translation. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Duality and Pattern recognition.

His Test research is multidisciplinary, incorporating perspectives in Coreference, Information access, Patent application, Privilege and Custodians. Douglas W. Oard interconnects Entity linking, Traceability and Selection in the investigation of issues within Natural language processing. Douglas W. Oard combines subjects such as Question answering, Semantic analysis and Mathematics education with his study of Clef.

Between 2015 and 2021, his most popular works were:

  • Tangent-CFT: An Embedding Model for Mathematical Formulas (19 citations)
  • Characterizing searches for mathematical concepts (10 citations)
  • Patent-Related Tasks at NTCIR (6 citations)

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

  • Artificial intelligence
  • Machine learning
  • Law

Douglas W. Oard mainly focuses on Information retrieval, Test, Relevance, Entity linking and Artificial intelligence. His Information retrieval research includes themes of As is and Index. Douglas W. Oard has included themes like Question answering, Learning to rank and Clef in his Relevance study.

His studies link Natural language processing with Entity linking. The concepts of his Natural language processing study are interwoven with issues in Query by Example, Linguistic Data Consortium and Coreference. Many of his studies on Artificial intelligence apply to Pattern recognition as well.

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.

Top Publications

Implicit Feedback for Recommender Systems

Douglas W Oard;Jinmook Kim.
(1998)

518 Citations

A survey of information retrieval and filtering methods

Christos Faloutsos;Douglas W. Oard.
(1995)

339 Citations

Pairwise Document Similarity in Large Collections with MapReduce

Tamer Elsayed;Jimmy Lin;Douglas Oard.
meeting of the association for computational linguistics (2008)

294 Citations

Cross-Language Information Retrieval.

Douglas W. Oard;Anne R. Diekema.
Annual Review of Information Science and Technology (ARIST) (1998)

284 Citations

ENSM-SE at CLEF 2006 : Fuzzy Proximity Method with an Adhoc Influence Function in Evaluation of Multilingual and Multi-modal Information Retrieval 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain

Carol Peters;Paul Clough;Fredric C. Gey;Jussi Karlgren.
Lecture Notes in Computer Science (2007)

273 Citations

Confidentiality-preserving rank-ordered search

Ashwin Swaminathan;Yinian Mao;Guan-Ming Su;Hongmei Gou.
workshop on storage security and survivability (2007)

250 Citations

Advances in Multilingual and Multimodal Information Retrieval

Carol Peters;Valentin Jijkoun;Thomas Mandl;Henning Müller.
(2008)

230 Citations

A survey of multilingual text retrieval

Douglas W. Oard;Bonnie J. Dorr.
(1996)

229 Citations

Textual Data Mining to Support Science and Technology Management

Paul Losiewicz;Douglas W. Oard;Ronald N. Kostoff.
intelligent information systems (2000)

226 Citations

The State of the Art in Text Filtering

Douglas W. Oard.
User Modeling and User-adapted Interaction (1997)

205 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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