2015 - ACM Distinguished Member
Charles L. A. Clarke mainly investigates Information retrieval, Artificial intelligence, Relevance, Ranking and Search engine. Charles L. A. Clarke combines subjects such as Track, World Wide Web and Measure with his study of Information retrieval. The study incorporates disciplines such as Simplicity and Novelty in addition to Measure.
His biological study spans a wide range of topics, including Machine learning, Rank and Natural language processing. He works mostly in the field of Ranking, limiting it down to concerns involving Data mining and, occasionally, Simple API for XML, Efficient XML Interchange, XML Signature, Streaming XML and XML framework. His studies deal with areas such as Rewrite engine, Web crawler and Snippet as well as Search engine.
His main research concerns Information retrieval, World Wide Web, Data mining, Artificial intelligence and Search engine. Information retrieval and Context are frequently intertwined in his study. When carried out as part of a general World Wide Web research project, his work on The Internet, Social media and Information access is frequently linked to work in Track, therefore connecting diverse disciplines of study.
His Data mining research incorporates elements of Ranking, Cluster analysis and Pattern recognition. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Natural language processing. His Search engine research focuses on Rank and how it connects with Learning to rank.
Charles L. A. Clarke spends much of his time researching World Wide Web, Information retrieval, Search engine, Relevance and Data mining. His World Wide Web research integrates issues from Question answering, Context and Internet privacy. The study incorporates disciplines such as restrict and Pooling in addition to Information retrieval.
The Search engine study combines topics in areas such as Visualization, Eye tracking and Gaze. His Relevance research is multidisciplinary, incorporating elements of Ranking, Session, Set, Applied psychology and Push technology. Charles L. A. Clarke has researched Data mining in several fields, including Ranking, Proof of concept, Latency and Algorithm Selection.
Information retrieval, Data mining, Relevance, Social media and Search engine are his primary areas of study. His Information retrieval research incorporates themes from Context, Point of interest and Pooling. His Data mining study also includes fields such as
His work carried out in the field of Relevance brings together such families of science as Ranking, Ranking and Tensor. In his research on the topic of Social media, Human–computer interaction is strongly related with Push technology. He has included themes like Conversational search, Multimedia and Interface in his Search engine study.
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.
Novelty and diversity in information retrieval evaluation
Charles L.A. Clarke;Maheedhar Kolla;Gordon V. Cormack;Olga Vechtomova.
international acm sigir conference on research and development in information retrieval (2008)
Information Retrieval: Implementing and Evaluating Search Engines
Stefan Büttcher;Charles Clarke;Gordon V. Cormack.
(2010)
Overview of the TREC 2009 Web Track
Charles L. A. Clarke;Nick Craswell;Ian Soboroff.
text retrieval conference (2009)
Efficient and effective spam filtering and re-ranking for large web datasets
Gordon V. Cormack;Mark D. Smucker;Charles L. Clarke.
Information Retrieval (2011)
Exploiting redundancy in question answering
Charles L. A. Clarke;Gordon V. Cormack;Thomas R. Lynam.
international acm sigir conference on research and development in information retrieval (2001)
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Gordon V. Cormack;Charles L A Clarke;Stefan Buettcher.
international acm sigir conference on research and development in information retrieval (2009)
Frequency estimates for statistical word similarity measures
Egidio Terra;C. L. A. Clarke.
north american chapter of the association for computational linguistics (2003)
Relevance ranking for one to three term queries
Charles L. A. Clarke;Gordon V. Cormack;Elizabeth A. Tudhope.
Information Processing and Management (2000)
Efficient construction of large test collections
Gordon V. Cormack;Christopher R. Palmer;Charles L. A. Clarke.
international acm sigir conference on research and development in information retrieval (1998)
An Algebra for Structured Text Search and a Framework for its Implementation
Charles L. A. Clarke;Gordon V. Cormack;Forbes J. Burkowski.
The Computer Journal (1995)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
University of Waterloo
University of Amsterdam
University of Waterloo
National Institute of Standards and Technology
Microsoft (United States)
Emory University
National Institute of Standards and Technology
Microsoft (United States)
University of Glasgow
Carnegie Mellon University
Princeton University
University of North Carolina at Chapel Hill
RWTH Aachen University
Autonomous University of Barcelona
Cornell University
Kyoto University
University of Helsinki
Pennsylvania State University
Nord University
University of Maryland, College Park
Obihiro University of Agriculture and Veterinary Medicine
University of Manchester
Claremont Graduate University
Wayne State University
University of Glasgow
Lancaster University