What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Database
- Programming language
Clement Yu mainly investigates Information retrieval, Web search query, Search engine, Search analytics and Artificial intelligence.
The study incorporates disciplines such as Set and Database in addition to Information retrieval.
His Web query classification study, which is part of a larger body of work in Web search query, is frequently linked to Crawling, bridging the gap between disciplines.
His Search analytics research is multidisciplinary, relying on both Metasearch engine and Semantic search.
His Artificial intelligence research focuses on Natural language processing and how it relates to Identification, Scope and Negation.
His research in Query expansion intersects with topics in Query language, Web service, Ranking and Query optimization.
His most cited work include:
- Personalized Web search for improving retrieval effectiveness (386 citations)
- Building efficient and effective metasearch engines (374 citations)
- Effective keyword search in relational databases (329 citations)
What are the main themes of his work throughout his whole career to date?
Clement Yu mostly deals with Information retrieval, Search engine, Data mining, Metasearch engine and Query expansion.
His Information retrieval research includes themes of Database and Artificial intelligence.
His Search engine study combines topics in areas such as Web page and Search engine indexing.
His study in Data mining is interdisciplinary in nature, drawing from both Deep Web, Set, Relevance and Cluster analysis.
His work carried out in the field of Metasearch engine brings together such families of science as Local search and The Internet.
The concepts of his Query expansion study are interwoven with issues in Ranking, Natural language processing, Query language, Web query classification and Ranking.
He most often published in these fields:
- Information retrieval (53.20%)
- Search engine (22.66%)
- Data mining (18.23%)
What were the highlights of his more recent work (between 2007-2017)?
- Information retrieval (53.20%)
- Query expansion (15.27%)
- Artificial intelligence (14.78%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Information retrieval, Query expansion, Artificial intelligence, Natural language processing and Web search query.
Metasearch engine and Search engine are the core of his Information retrieval study.
The various areas that he examines in his Query expansion study include Document retrieval and Ranking.
Clement Yu has researched Natural language processing in several fields, including Human–computer information retrieval, Word and Task.
His Web search query research includes elements of Web service, Web modeling and Data integration, Database.
His study looks at the relationship between Web query classification and fields such as Query optimization, as well as how they intersect with chemical problems.
Between 2007 and 2017, his most popular works were:
- The effect of negation on sentiment analysis and retrieval effectiveness (151 citations)
- A hierarchical approach to model web query interfaces for web source integration (72 citations)
- Construction of a sentimental word dictionary (60 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Database
His primary scientific interests are in Information retrieval, Query expansion, Artificial intelligence, Natural language processing and Ranking.
In his articles, he combines various disciplines, including Information retrieval and Data collection.
His Query expansion research integrates issues from Web search query, Data integration and Query optimization.
His research in the fields of Word overlaps with other disciplines such as Synonym.
His studies deal with areas such as Document retrieval, Ranking, Classifier and Extension as well as Ranking.
His work deals with themes such as Tree structure, Web service and Web query classification, which intersect with Web page.
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