2011 - Member of the Royal Irish Academy
Barry Smyth mainly focuses on World Wide Web, Recommender system, Case-based reasoning, Information retrieval and Artificial intelligence. His study in World Wide Web is interdisciplinary in nature, drawing from both Multimedia, Service and Information system. Particularly relevant to Collaborative filtering is his body of work in Recommender system.
His work carried out in the field of Case-based reasoning brings together such families of science as Risk analysis, Software design, Reasoning system and Competence. His Information retrieval research incorporates elements of Ranking, User-generated content, Popularity and Real-time web. In his study, Context is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence.
World Wide Web, Recommender system, Information retrieval, Artificial intelligence and Case-based reasoning are his primary areas of study. His study on World Wide Web is mostly dedicated to connecting different topics, such as Multimedia. He works on Recommender system which deals in particular with Collaborative filtering.
His Information retrieval research includes themes of Service and Profiling. His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Competence. His biological study spans a wide range of topics, including Adaptation, Process and Reasoning system.
Barry Smyth focuses on Recommender system, World Wide Web, Data science, Information retrieval and Artificial intelligence. He is involved in the study of Recommender system that focuses on Collaborative filtering in particular. In the field of World Wide Web, his study on Crowdsourcing overlaps with subjects such as Preference data.
As a part of the same scientific study, Barry Smyth usually deals with the Data science, concentrating on Process and frequently concerns with Ranking. His Artificial intelligence study frequently draws connections between adjacent fields such as Machine learning. His study in Case-based reasoning is interdisciplinary in nature, drawing from both Marathon running and Feature.
Barry Smyth mainly investigates Recommender system, World Wide Web, Sentiment analysis, Artificial intelligence and Race. His Recommender system study results in a more complete grasp of Information retrieval. His work deals with themes such as User experience design and Feature, which intersect with World Wide Web.
In Sentiment analysis, Barry Smyth works on issues like Context, which are connected to Ranking. His Artificial intelligence research incorporates themes from Machine learning and Collaborative filtering. His research in Knowledge representation and reasoning focuses on subjects like Case-based reasoning, which are connected to Task and Operations research.
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.
Trust in recommender systems
John O'Donovan;Barry Smyth.
intelligent user interfaces (2005)
Retrieval, reuse, revision and retention in case-based reasoning
Ramon Lopez De Mantaras;David McSherry;Derek Bridge;David Leake.
Knowledge Engineering Review (2005)
Recommending twitter users to follow using content and collaborative filtering approaches
John Hannon;Mike Bennett;Barry Smyth.
conference on recommender systems (2010)
Similarity vs. Diversity
Barry Smyth;Paul McClave.
international conference on case based reasoning (2001)
Using twitter to recommend real-time topical news
Owen Phelan;Kevin McCarthy;Barry Smyth.
conference on recommender systems (2009)
Recommendation to groups
Anthony Jameson;Barry Smyth.
The adaptive web (2007)
Remembering to forget: a competence-preserving case deletion policy for case-based reasoning systems
Barry Smyth;Mark T. Keane.
international joint conference on artificial intelligence (1995)
Case-based recommender systems
Derek Bridge;Mehmet H. Göker;Lorraine McGinty;Barry Smyth.
Knowledge Engineering Review (2005)
A personalized television listings service
Barry Smyth;Paul Cotter.
Communications of The ACM (2000)
Understanding the intent behind mobile information needs
Karen Church;Barry Smyth.
intelligent user interfaces (2009)
Profile was last updated on December 6th, 2021.
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