Information retrieval, Artificial intelligence, World Wide Web, Machine learning and Data mining are his primary areas of study. In general Information retrieval, his work in Ranking and Query expansion is often linked to Diversification and Track linking many areas of study. His research integrates issues of Ranking and Heuristics in his study of Ranking.
As a part of the same scientific family, Craig Macdonald mostly works in the field of Query expansion, focusing on Web query classification and, on occasion, Sargable and Query optimization. He interconnects Baseline and Natural language processing in the investigation of issues within Artificial intelligence. He has included themes like Text Retrieval Conference and Information seeking in his World Wide Web study.
Craig Macdonald focuses on Information retrieval, Artificial intelligence, World Wide Web, Ranking and Search engine. His Information retrieval research focuses on subjects like Social media, which are linked to Crowdsourcing. His Artificial intelligence study combines topics in areas such as Machine learning, Recommender system and Natural language processing.
His study of Blogosphere is a part of World Wide Web. His multidisciplinary approach integrates Ranking and Voting in his work. His biological study deals with issues like Query optimization, which deal with fields such as Sargable.
His primary areas of investigation include Information retrieval, Artificial intelligence, Machine learning, Recommender system and Classifier. Learning to rank and Ranking are subfields of Information retrieval in which his conducts study. His Artificial intelligence research is multidisciplinary, relying on both Ranking and Natural language processing.
Craig Macdonald combines subjects such as Feedback loop and Bayesian probability with his study of Machine learning. His Recommender system research incorporates elements of Recurrent neural network and Leverage. His studies in Classifier integrate themes in fields like Active learning, Information sensitivity, Personally identifiable information and Training set.
His primary areas of study are Artificial intelligence, Information retrieval, Machine learning, Social media and Recommender system. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Personally identifiable information and Natural language processing. Craig Macdonald brings together Information retrieval and Multiple days to produce work in his papers.
His work deals with themes such as Classifier, Representation, Inference and Bayesian inference, which intersect with Machine learning. His biological study spans a wide range of topics, including Ranking, Recurrent neural network and Human–computer interaction. Craig Macdonald has researched Ranking in several fields, including Predictive modelling, Leverage and Selection.
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.
Terrier information retrieval platform
Iadh Ounis;Gianni Amati;Vassilis Plachouras;Ben He.
european conference on information retrieval (2005)
Exploiting query reformulations for web search result diversification
Rodrygo L.T. Santos;Craig Macdonald;Iadh Ounis.
the web conference (2010)
Overview of the TREC-2008 Blog Track
Iadh Ounis;Craig Macdonald;Ian Soboroff.
text retrieval conference (2008)
Overview of the TREC 2006 Blog Track
Iadh Ounis;Craig Macdonald;Maarten de Rijke;Gilad Mishne.
text retrieval conference (2006)
Overview of the TREC-2007 Blog Track
Craig Macdonald;Iadh Ounis;Ian Soboroff.
text retrieval conference (2007)
Voting for candidates: adapting data fusion techniques for an expert search task
Craig Macdonald;Iadh Ounis.
conference on information and knowledge management (2006)
The TREC Blogs06 Collection: Creating and Analysing a Blog Test Collection
C. Macdonald;I. Ounis.
(2006)
Overview of the TREC-2011 Microblog Track
Iadh Ounis;Craig Macdonald;Jimmy Lin;Ian Soboroff.
text retrieval conference (2011)
Overview of the TREC-2009 Blog Track
Craig Macdonald;Iadh Ounis;Ian Soboroff.
text retrieval conference (2009)
Overview of the TREC-2012 Microblog Track.
Ian Soboroff;Iadh Ounis;Craig Macdonald;Jimmy J. Lin.
text retrieval conference (2012)
University of Glasgow
National Institute of Standards and Technology
University of Waterloo
University of Waterloo
Microsoft (United States)
Institute of Information Science and Technologies
Bloomberg LP
University of Glasgow
Sapienza University of Rome
University of Michigan–Ann Arbor
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
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: