Supporting People in Finding Information: Hybrid Recommender Systems and Goal-Based Structuring

Keywords

Structuring, Computer science, Recommender system, Publication, Interface (matter)

References

• Identifying Attack Models for Secure RecommendationRobin Burke, Bamshad Mobasher, Roman Zabicki — 2004
• Human-computer interaction (2nd ed.)Alan Dix, Janet L. Finley, Gregory D. Abowd — 1998
• The State of the Art in Text FilteringDouglas W. Oard — 1997
• Experiments with a Recommendation Technique that Learns Category InterestsMark van Setten — 2002
• Personalization and privacyEugene Volokh — 2000
• Knowledge-based recommender systemsRobin Burke — 2000
• Confidence Displays and Training in Recommender SystemsSean M. McNee, Shyong K. Lam, Catherine Guetzlaff — 2003
• How and Why People Watch TV: Implications for the Future of Interactive TelevisionBarbara Lee, Robert S. Lee — 1995
• Hybrid Recommender Systems for Electronic CommerceThomas Tran, Robin Cohen — 2000
• Toward parallel and distributed learning by meta-learningPhilip K. Chan, Salvatore J. Stolfo — 1993
• Hybrid Recommender Systems: Survey and ExperimentsRobin Burke — 2002
• An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering AlgorithmsJon Herlocker, Joseph A. Konstan, John Riedl — 2002
• User Interface Design for ProgrammersAvram Joel Spolsky — 2001
• Modeling a Dialogue Strategy for Personalized Movie RecommendationsPontus Wärnestål — 2005
• Combining Content-Based and Collaborative Filters in an Online NewspaperMark Claypool, Anuja Gokhale, Tim Miranda — 1999
• Providing architectural support for building context-aware applicationsAnind K. Dey, Gregory D. Abowd — 2000
• Understanding consumer decision making : the means-end approach to marketing and advertising strategyT. Reynolds, J. Olson — 2001
• Understanding and improving automated collaborative filtering systemsJoseph A. Konstan, Jonathan L. Herlocker — 2000
• TV Content Recommender SystemSrinivas Gutta, Kaushal Kurapati, K. P. Lee — 2000
• Information Retrieval InteractionPeter Ingwersen — 1992

Cited by

• Clustering approach based on feature weighting for recommendation system in movie domainNabizadeh Rafsanjani, Amir Hossein — 2013
• Explanation Interfaces in Recommender SystemsNing Xu — 2007
• Cognition in Context - The effect of information and communication support on task performance of distributed professionalsMargaretha Catharina Maria Biemans — 2006
• Formal concept analysis and tag recommendations in collaborative tagging systemsRobert Jäschke — 2011
• Experimenting switching hybrid recommender systemsMustansar Ali Ghazanfar — 2015
• Context-Aware Personalization for Mobile MultimediaAbayomi Otebolaku — 2015
• Recommendation strategies for e-learning: preliminary effects of a personal recommender system for lifelong learnersHendrik Drachsler, Hans Hummel, Van den Berg, Bert — 2007
• Effects of the ISIS Recommender System for Navigation Support in self-organised Learning NetworksHendrik Drachsler, Hans Hummel, Bert van den Berg — 2009
• Recommender system performance evaluation and prediction an information retrieval perspectiveAlejandro Bellogín Kouki — 2014
• Recommending multimedia web services in a multi-device environmentDomenico Rosaci, Giuseppe M. L. Sarnè — 2013
• Hybreed: A software framework for developing context-aware hybrid recommender systemsTim Hussein, Timm Linder, Werner Gaulke — 2014
• Incorporating user motivations to design for video taggingLex van Velsen, Mark Melenhorst — 2009
• Dynamic generation of personalized hybrid recommender systemsSimon Dooms — 2013
• Cross Domain Framework for Implementing Recommendation Systems Based on Context Based Implicit Negative FeedbackMaitri Jhaveri, Jyoti Pareek — 2012
• Analysis and Classification of Multi-Criteria Recommender SystemsNikos Manouselis, Constantina Costopoulou — 2007
• Semantic-based framework for personalised ambient mediaLora Aroyo, Pieter Bellekens, Martin Björkman — 2006
• Hybrid Content-Based Collaborative-Filtering Music RecommendationsHugo Siles Del Castillo — 2007
• The effects of transparency on trust in and acceptance of a content-based art recommenderHenriette Cramer, Vanessa Evers, Satyan Ramlal — 2008
• Robust, scalable, and practical algorithms for recommender systemsMustansar Ali Ghazanfar — 2012
• Combining social-based and information-based approaches for personalised recommendation on sequencing learning activitiesHans Hummel, Bert van den Berg, Adriana Berlanga — 2007

Related papers

• Hybrid Recommender Systems: Survey and ExperimentsRobin Burke — 2002
• Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensionsGediminas Adomavičius, Alexander Tuzhilin — 2005
• Evaluating collaborative filtering recommender systemsJonathan L. Herlocker, Joseph A. Konstan, Loren Terveen — 2004
• A Framework for Collaborative, Content-Based and Demographic FilteringMichael J. Pazzani — 1999
• Content-boosted collaborative filtering for improved recommendationsPrem Melville, Raymod J. Mooney, Ramadass Nagarajan — 2002
• Fab: content-based, collaborative recommendationMarko Balabanović, Yoav Shoham — 1997
• GroupLensPaul Resnick, Neophytos Iacovou, Mitesh Suchak — 1994
• Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and modelHendrik Drachsler, Hans Hummel, Rob Koper — 2008
• Amazon.com Recommendations: Item-to-Item Collaborative FilteringGreg Linden, Brent Smith, Jeremy York — 2003
• Social information filtering: algorithms for automating “word of mouth”Upendra Shardanand, Pattie Maes — 1995