Results 281 to 290 of about 85,662 (301)
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Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, 2018
Recommender systems for groups are becoming increasingly popular since many information needs originate from group and social activities, such as listening to music, watching movies, traveling, etc. There has been substantial progress on systems which recommend items to groups of users. However, many challenges remain.
Delic, Amra, Masthoff, Judith
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Recommender systems for groups are becoming increasingly popular since many information needs originate from group and social activities, such as listening to music, watching movies, traveling, etc. There has been substantial progress on systems which recommend items to groups of users. However, many challenges remain.
Delic, Amra, Masthoff, Judith
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2019
Personalization increasingly mediates the experience of users on the Web. Online platforms and organizations use personalization services to retain users, achieve longer user or customer engagement and, ultimately, higher profits. Cast in this light, personalization is a ubiquitous modality by means of which organizations seek to structure interaction
Alaimo, Cristina, Kallinikos, Jannis
+5 more sources
Personalization increasingly mediates the experience of users on the Web. Online platforms and organizations use personalization services to retain users, achieve longer user or customer engagement and, ultimately, higher profits. Cast in this light, personalization is a ubiquitous modality by means of which organizations seek to structure interaction
Alaimo, Cristina, Kallinikos, Jannis
+5 more sources
2023
Recommendation systems are critical tools used by marketing departments to provide customers with product recommendations. Data scientists also use recommendation system analysis to assess the effectiveness of product and service suggestions. There are two types of recommendation systems: content-based and collaborative filtering.
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Recommendation systems are critical tools used by marketing departments to provide customers with product recommendations. Data scientists also use recommendation system analysis to assess the effectiveness of product and service suggestions. There are two types of recommendation systems: content-based and collaborative filtering.
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Proceedings of the 10th ACM Conference on Recommender Systems, 2016
Group recommender systems provide suggestions in contexts in which people operate in groups. The goal of this tutorial is to provide the RecSys audience with an overview on group recommendation. We will first formally introduce the problem of producing recommendations to groups, then present a survey based on the tasks performed by these systems.
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Group recommender systems provide suggestions in contexts in which people operate in groups. The goal of this tutorial is to provide the RecSys audience with an overview on group recommendation. We will first formally introduce the problem of producing recommendations to groups, then present a survey based on the tasks performed by these systems.
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Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, 2009
Nowadays, recommendation systems are definitely a necessity in the websites not just an auxiliary feature, especially for commercial websites and web sites with large information services. Recommendation systems use models constructed by applying statistical and data mining approaches on derived data from websites. In this paper we propose a new hybrid
Saeed R. Aghabozorgi, Teh Ying Wah
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Nowadays, recommendation systems are definitely a necessity in the websites not just an auxiliary feature, especially for commercial websites and web sites with large information services. Recommendation systems use models constructed by applying statistical and data mining approaches on derived data from websites. In this paper we propose a new hybrid
Saeed R. Aghabozorgi, Teh Ying Wah
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XRDS: Crossroads, The ACM Magazine for Students, 2020
Vladimir Shikhman, David Müller
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Vladimir Shikhman, David Müller
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2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07), 2007
Recommender systems give advice about products, information or services users might be interested in. They are intelligent applications to assist users in a decision-making process where they want to choose one item amongst a potentially overwhelming set of alternative products or services.
Hannes Werthner +2 more
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Recommender systems give advice about products, information or services users might be interested in. They are intelligent applications to assist users in a decision-making process where they want to choose one item amongst a potentially overwhelming set of alternative products or services.
Hannes Werthner +2 more
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This study conducts a quantitative comparison between fuzzy logic expert systems and traditional recommender systems for movie recommendations, with a focus on capturing a wide variety of human consumer trends. Traditional recommender systems, characterized by their deterministic approach to user preferences, are contrasted with fuzzy logic expert ...
Pablo Castells, Dietmar Jannach
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Pablo Castells, Dietmar Jannach
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Recommendation systems are critical tools used by marketing departments to provide customers with product recommendations. Data scientists also use recommendation system analysis to assess the effectiveness of product and service suggestions. There are two types of recommendation systems: content-based and collaborative filtering.
openaire +1 more source
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