What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Linguistics
- Programming language
Yorick Wilks spends much of his time researching Natural language processing, Artificial intelligence, Information extraction, Semantics and Information retrieval.
In Natural language processing, Yorick Wilks works on issues like Linguistics, which are connected to Meaning.
The various areas that Yorick Wilks examines in his Artificial intelligence study include Domain and Field.
The Information extraction study combines topics in areas such as Information science, Named-entity recognition, Information integration and Component.
His Semantics research is multidisciplinary, relying on both Phrase, Representation and Metaphor.
His Information retrieval research integrates issues from Annotation, Context and Image retrieval.
His most cited work include:
- Data Driven Ontology Evaluation (317 citations)
- A Preferential, Pattern-Seeking, Semantics for Natural Language Inference (290 citations)
- MAKING PREFERENCES MORE ACTIVE (234 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Natural language processing, Linguistics, Machine translation and Natural language.
Artificial intelligence connects with themes related to Representation in his study.
He studies Parsing which is a part of Natural language processing.
His Linguistics study which covers Cognitive science that intersects with Sociolinguistics.
His study on Information extraction is covered under Information retrieval.
His Information retrieval research focuses on subjects like Annotation, which are linked to Semantic Web.
He most often published in these fields:
- Artificial intelligence (49.40%)
- Natural language processing (40.77%)
- Linguistics (21.58%)
What were the highlights of his more recent work (between 2007-2019)?
- Artificial intelligence (49.40%)
- Natural language processing (40.77%)
- Linguistics (21.58%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Natural language processing, Linguistics, Machine translation and World Wide Web.
His research in Artificial intelligence intersects with topics in Computational semantics and Meaning.
His Natural language processing research is multidisciplinary, incorporating elements of Resource and RDF.
Yorick Wilks combines subjects such as Epistemology, Task and Point with his study of Linguistics.
He focuses mostly in the field of Machine translation, narrowing it down to topics relating to Lexical item and, in certain cases, Word sense.
His World Wide Web study integrates concerns from other disciplines, such as Multimedia, Conversation and Avatar.
Between 2007 and 2019, his most popular works were:
- Close Engagements with Artificial Companions: Key Social, Psychological, Ethical and Design Issues (81 citations)
- Machine Translation: Its Scope and Limits (48 citations)
- The Semantic Web: Apotheosis of Annotation, but What Are Its Semantics? (41 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Linguistics
- Programming language
His primary scientific interests are in Artificial intelligence, Natural language processing, Multimedia, Human–computer interaction and Social psychology.
Yorick Wilks undertakes interdisciplinary study in the fields of Artificial intelligence and Statistical relational learning through his research.
His work deals with themes such as Domain and RDF, Semantic Web, which intersect with Natural language processing.
His study on Multimedia also encompasses disciplines like
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Ambient intelligence which is related to area like Scalability, Architecture, Porting, Agent-oriented software engineering and Robustness,
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Table together with World Wide Web.
Yorick Wilks studied Social psychology and Robot that intersect with Internet privacy, Key and Software.
His Annotation research also works with subjects such as
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Content together with Utterance,
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Language model that connect with fields like Semantics.
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