Results 1 - 10 of 509

Content-Based Book Recommending Using Learning for Text Categorization

by Raymond J. Mooney, Loriene Roy - IN PROCEEDINGS OF THE FIFTH ACM CONFERENCE ON DIGITAL LIBRARIES , 1999
"... Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most existing recommender systems use collaborative filtering methods that base recommendations on other users' preferences. ..."
Abstract - Cited by 334 (8 self) - Add to MetaCart
Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most existing recommender systems use collaborative filtering methods that base recommendations on other users' preferences

A personalized system for conversational recommendations,

by Cynthia A Thompson , Mehmet H Göker , Pat Langley - Journal of Artificial Intelligence Research, , 2004
"... Abstract Increased computing power and the Web have made information widely accessible. In turn, this has encouraged the development of recommendation systems that help users find items of interest, such as books or restaurants. Such systems are more useful when they personalize themselves to each ..."
Abstract - Cited by 75 (1 self) - Add to MetaCart
Abstract Increased computing power and the Web have made information widely accessible. In turn, this has encouraged the development of recommendation systems that help users find items of interest, such as books or restaurants. Such systems are more useful when they personalize themselves to each

Personalized news recommendation based on click behavior

by Jiahui Liu, Peter Dolan, Elin Rønby Pedersen - In Proceedings of the 15th International Conference on Intelligent User Interfaces (IUI10 , 2010
"... Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help users find the articles that are interesting to read. In this paper, we present our research on developing personalized news ..."
Abstract - Cited by 57 (2 self) - Add to MetaCart
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help users find the articles that are interesting to read. In this paper, we present our research on developing personalized news

Recommendation and personalization: a survey

by Saverio Perugini, Marcos André Gonçalves , 2002
"... Recommendation and personalization attempt to reduce information overload and retain customers. While research in both recommender systems and personalization grew mainly out of information retrieval, both areas have emerged from nascent levels to veritable and challenging research areas in their ow ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
approach toward studying recommendation and personalization. Specifically, we present three major representative personalization themes: rec-ommendation; induction, exploration, and exploitation of social networks; and personalization of information access. We unify the presentation of the three themes

Travel recommender systems

by Francesco Ricci - IEEE Intelligent Systems
"... Mobile phones are becoming a primary platform for information access and when coupled with recommender systems technologies they can become key tools for mobile users both for leisure and business applications. Recommendation techniques can increase the usability of mobile systems providing personal ..."
Abstract - Cited by 68 (15 self) - Add to MetaCart
Mobile phones are becoming a primary platform for information access and when coupled with recommender systems technologies they can become key tools for mobile users both for leisure and business applications. Recommendation techniques can increase the usability of mobile systems providing

Open Access Friends Recommendation with Rating Side Information

by Xiang Hu, Wengdong Wang, Xiangyang Gong, Bai Wang, Xirong Que, Hongke Xia
"... Abstract: With the broad application of web 2.0 technology, various kinds of online social networks arise at present. The emergence of social networks not only helps the public to facilitate the sharing and communicating, but also helps them to know more new friends from cyberspace social circle. Th ..."
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to capture interest relevance (interest similarity) between persons, makes use of Gaussian process to generate the users ’ profile vectors, and eventually achieves a recommendation method having the capability of commending friends with common interests. Experiments show that our method outperforms the art

The Wasabi Personal Shopper: A Case-Based Recommender System

by Robin Burke - IN PROCEEDINGS OF THE 11TH NATIONAL CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE , 1999
"... The Wasabi Personal Shopper (WPS) is a domainindependent database browsing tool designed for on-line information access, particularly for electronic product catalogs. Typically, web-based catalogs rely either on text search or query formulation. WPS introduces an alternative form of access via ..."
Abstract - Cited by 42 (7 self) - Add to MetaCart
The Wasabi Personal Shopper (WPS) is a domainindependent database browsing tool designed for on-line information access, particularly for electronic product catalogs. Typically, web-based catalogs rely either on text search or query formulation. WPS introduces an alternative form of access via

Exploiting contextual information from event logs for personalized recommendation

by Dongjoo Lee Sung Eun Park - In Computer and Information Science, Studies in Computational Intelligence , 2010
"... Abstract. Nowadays, recommender systems are widely used in various domains to help customers access to more satisfying products or services. It is expected that exploiting customers ’ contextual information can improve the quality of rec-ommendation results. Most earlier researchers assume that they ..."
Abstract - Cited by 8 (6 self) - Add to MetaCart
Abstract. Nowadays, recommender systems are widely used in various domains to help customers access to more satisfying products or services. It is expected that exploiting customers ’ contextual information can improve the quality of rec-ommendation results. Most earlier researchers assume

Recommended Citation

by Record Book Of The Erodelphian, Jack L. Dickinson , 2012
"... Part of the Education Commons, and the History Commons This Personal Paper is brought to you for free and open access by the Library Special Collections at Marshall Digital Scholar. It has been accepted for inclusion in Manuscripts by an authorized administrator of Marshall Digital Scholar. For more ..."
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Part of the Education Commons, and the History Commons This Personal Paper is brought to you for free and open access by the Library Special Collections at Marshall Digital Scholar. It has been accepted for inclusion in Manuscripts by an authorized administrator of Marshall Digital Scholar

The sensitivities of user profile information in music recommender systems

by Evelien Perik, Boris De Ruyter, Panos Markopoulos, Berry Eggen - In Proceedings of Private, Security, Trust , 2004
"... Abstract—Personalized services can cause privacy concerns, due to the acquisition, storage and application of sensitive personal information. This paper describes empirical research into the factors influencing the trade-off between the perceived benefits of personalization and the privacy ‘costs ’ ..."
Abstract - Cited by 8 (2 self) - Add to MetaCart
’ experienced by individuals. The experiment in question concerns a music recommender system accessed over the Internet. Recommendations are based on two different types of information about their user: music preferences and personality. Users are offered several levels of disclosure for this information
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