The Experts below are selected from a list of 149913 Experts worldwide ranked by ideXlab platform
Martijn C. Willemsen - One of the best experts on this subject based on the ideXlab platform.
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RecSys - Workshop on Human Decision Making in recommender systems: Decisions@RecSys'13
Proceedings of the 7th ACM conference on Recommender systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:A primary function of recommender systems is to help their users to make better choices and Decisions. The overall goal of the workshop is to analyse and discuss novel techniques and approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios. The submitted papers discuss a wide range of topics from core algorithmic issues to the management of the Human computer interaction.
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RecSys - RecSys'12 workshop on Human Decision Making in recommender systems
Proceedings of the sixth ACM conference on Recommender systems - RecSys '12, 2012Co-Authors: Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:Interacting with a recommender system means to take different Decisions such as selecting an item from a recommendation list, selecting a specific item feature value (e.g., camera's size, zoom) as a search criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these situations, users face a Decision task. This workshop (Decisions@RecSys) focuses on approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios.
Alexander Felfernig - One of the best experts on this subject based on the ideXlab platform.
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RecSys - Workshop on Human Decision Making in recommender systems: Decisions@RecSys'13
Proceedings of the 7th ACM conference on Recommender systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:A primary function of recommender systems is to help their users to make better choices and Decisions. The overall goal of the workshop is to analyse and discuss novel techniques and approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios. The submitted papers discuss a wide range of topics from core algorithmic issues to the management of the Human computer interaction.
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Human Decision Making and Recommender Systems
ACM Transactions on Interactive Intelligent Systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni SemeraroAbstract:Recommender Systems have already proved to be valuable for coping with the information overload problem\ud in several application domains. They provide people with suggestions for items which are likely to be\ud of interest for them; hence, a primary function of recommender systems is to help people make good choices\ud and Decisions. However, most previous research has focused on recommendation techniques and algorithms, and less attention has been devoted to the Decision Making processes adopted by the users and possibly supported by the system. There is still a gap between the importance that the community gives to the assessment of recommendation algorithms and the current range of ongoing research activities concerning\ud Human Decision Making. Different Decision-psychological phenomena can influence the Decision Making of users of recommender systems, and research along these lines is becoming increasingly important and popular.\ud This special issue highlights how the coupling of recommendation algorithms with the understanding of Human choice and Decision Making theory has the potential to benefit research and practice on recommender systems and to enable users to achieve a good balance between Decision accuracy and Decision effort
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RecSys - RecSys'12 workshop on Human Decision Making in recommender systems
Proceedings of the sixth ACM conference on Recommender systems - RecSys '12, 2012Co-Authors: Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:Interacting with a recommender system means to take different Decisions such as selecting an item from a recommendation list, selecting a specific item feature value (e.g., camera's size, zoom) as a search criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these situations, users face a Decision task. This workshop (Decisions@RecSys) focuses on approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios.
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RecSys - RecSys'11 workshop on Human Decision Making in recommender systems
Proceedings of the fifth ACM conference on Recommender systems - RecSys '11, 2011Co-Authors: Alexander Felfernig, Li Chen, Monika MandlAbstract:Interacting with a recommender system means to take different Decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a Decision task. The major focuses of this workshop (Decisions@RecSys) were approaches for efficient Human Decision Making in different types of recommendation scenarios.
Marco De Gemmis - One of the best experts on this subject based on the ideXlab platform.
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RecSys - Workshop on Human Decision Making in recommender systems: Decisions@RecSys'13
Proceedings of the 7th ACM conference on Recommender systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:A primary function of recommender systems is to help their users to make better choices and Decisions. The overall goal of the workshop is to analyse and discuss novel techniques and approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios. The submitted papers discuss a wide range of topics from core algorithmic issues to the management of the Human computer interaction.
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Human Decision Making and Recommender Systems
ACM Transactions on Interactive Intelligent Systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni SemeraroAbstract:Recommender Systems have already proved to be valuable for coping with the information overload problem\ud in several application domains. They provide people with suggestions for items which are likely to be\ud of interest for them; hence, a primary function of recommender systems is to help people make good choices\ud and Decisions. However, most previous research has focused on recommendation techniques and algorithms, and less attention has been devoted to the Decision Making processes adopted by the users and possibly supported by the system. There is still a gap between the importance that the community gives to the assessment of recommendation algorithms and the current range of ongoing research activities concerning\ud Human Decision Making. Different Decision-psychological phenomena can influence the Decision Making of users of recommender systems, and research along these lines is becoming increasingly important and popular.\ud This special issue highlights how the coupling of recommendation algorithms with the understanding of Human choice and Decision Making theory has the potential to benefit research and practice on recommender systems and to enable users to achieve a good balance between Decision accuracy and Decision effort
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RecSys - RecSys'12 workshop on Human Decision Making in recommender systems
Proceedings of the sixth ACM conference on Recommender systems - RecSys '12, 2012Co-Authors: Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:Interacting with a recommender system means to take different Decisions such as selecting an item from a recommendation list, selecting a specific item feature value (e.g., camera's size, zoom) as a search criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these situations, users face a Decision task. This workshop (Decisions@RecSys) focuses on approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios.
Li Chen - One of the best experts on this subject based on the ideXlab platform.
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RecSys - Workshop on Human Decision Making in recommender systems: Decisions@RecSys'13
Proceedings of the 7th ACM conference on Recommender systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni Semeraro, Martijn C. WillemsenAbstract:A primary function of recommender systems is to help their users to make better choices and Decisions. The overall goal of the workshop is to analyse and discuss novel techniques and approaches for supporting effective and efficient Human Decision Making in different types of recommendation scenarios. The submitted papers discuss a wide range of topics from core algorithmic issues to the management of the Human computer interaction.
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Human Decision Making and Recommender Systems
ACM Transactions on Interactive Intelligent Systems, 2013Co-Authors: Li Chen, Marco De Gemmis, Alexander Felfernig, Pasquale Lops, Francesco Ricci, Giovanni SemeraroAbstract:Recommender Systems have already proved to be valuable for coping with the information overload problem\ud in several application domains. They provide people with suggestions for items which are likely to be\ud of interest for them; hence, a primary function of recommender systems is to help people make good choices\ud and Decisions. However, most previous research has focused on recommendation techniques and algorithms, and less attention has been devoted to the Decision Making processes adopted by the users and possibly supported by the system. There is still a gap between the importance that the community gives to the assessment of recommendation algorithms and the current range of ongoing research activities concerning\ud Human Decision Making. Different Decision-psychological phenomena can influence the Decision Making of users of recommender systems, and research along these lines is becoming increasingly important and popular.\ud This special issue highlights how the coupling of recommendation algorithms with the understanding of Human choice and Decision Making theory has the potential to benefit research and practice on recommender systems and to enable users to achieve a good balance between Decision accuracy and Decision effort
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RecSys - RecSys'11 workshop on Human Decision Making in recommender systems
Proceedings of the fifth ACM conference on Recommender systems - RecSys '11, 2011Co-Authors: Alexander Felfernig, Li Chen, Monika MandlAbstract:Interacting with a recommender system means to take different Decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a Decision task. The major focuses of this workshop (Decisions@RecSys) were approaches for efficient Human Decision Making in different types of recommendation scenarios.
Monika Mandl - One of the best experts on this subject based on the ideXlab platform.
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RecSys - RecSys'11 workshop on Human Decision Making in recommender systems
Proceedings of the fifth ACM conference on Recommender systems - RecSys '11, 2011Co-Authors: Alexander Felfernig, Li Chen, Monika MandlAbstract:Interacting with a recommender system means to take different Decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a Decision task. The major focuses of this workshop (Decisions@RecSys) were approaches for efficient Human Decision Making in different types of recommendation scenarios.
