What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Information retrieval
- World Wide Web
Nicholas J. Belkin focuses on Information retrieval, Relevance, Human–computer information retrieval, Cognitive models of information retrieval and Concept search.
Borrowing concepts from Relevance feedback, he weaves in ideas under Information retrieval.
His studies deal with areas such as Question answering and Management science as well as Relevance.
His work deals with themes such as Knowledge extraction, The Internet and Usability, which intersect with Human–computer information retrieval.
The study incorporates disciplines such as Information science and Information needs in addition to Cognitive models of information retrieval.
His study of Adversarial information retrieval is a part of Concept search.
His most cited work include:
- Information filtering and information retrieval: two sides of the same coin? (1230 citations)
- Ask for information retrieval: part I.: background and theory (715 citations)
- A case for interaction: a study of interactive information retrieval behavior and effectiveness (326 citations)
What are the main themes of his work throughout his whole career to date?
Nicholas J. Belkin mostly deals with Information retrieval, Human–computer information retrieval, Information seeking, Relevance and Personalization.
Nicholas J. Belkin focuses mostly in the field of Information retrieval, narrowing it down to matters related to Session and, in some cases, Human–computer interaction and Domain.
The various areas that Nicholas J. Belkin examines in his Human–computer information retrieval study include Question answering and Search engine.
His Information seeking research also works with subjects such as
- Variety, which have a strong connection to Usability,
- Knowledge management together with Data science.
In general Relevance, his work in Adversarial information retrieval is often linked to Relevance feedback linking many areas of study.
His biological study spans a wide range of topics, including Information science and Information needs.
He most often published in these fields:
- Information retrieval (49.10%)
- Human–computer information retrieval (18.47%)
- Information seeking (16.22%)
What were the highlights of his more recent work (between 2015-2020)?
- Information retrieval (49.10%)
- Session (10.81%)
- Personalization (14.86%)
In recent papers he was focusing on the following fields of study:
Nicholas J. Belkin mainly investigates Information retrieval, Session, Personalization, Journalism and Information seeking.
While working in this field, he studies both Information retrieval and Software.
His Session research incorporates elements of Variety and Task.
His research integrates issues of User experience design, Interactive search and Set in his study of Personalization.
His Information seeking study combines topics in areas such as Cognitive psychology, Knowledge management, Identification, Applied psychology and World Wide Web.
Nicholas J. Belkin has researched Human–computer interaction in several fields, including Mind map, Cognitive models of information retrieval and Search engine.
Between 2015 and 2020, his most popular works were:
- Predicting Information Seeking Intentions from Search Behaviors (16 citations)
- Extracting Information Seeking Intentions for Web Search Sessions (16 citations)
- People, Interacting with Information1 (16 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Information retrieval
- World Wide Web
Nicholas J. Belkin mainly focuses on Information seeking, Session, Journalism, Information retrieval and Personalization.
The Information seeking study combines topics in areas such as Knowledge management, Identification, Applied psychology, World Wide Web and Variety.
His Relevance research extends to the thematically linked field of Knowledge management.
The concepts of his World Wide Web study are interwoven with issues in User experience design, Use case, Analytics and Sensemaking.
His studies in Information retrieval integrate themes in fields like Similarity and Speech processing.
Nicholas J. Belkin has included themes like Usability and Text retrieval in his Personalization study.
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