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Advanced Search Results For "RECOMMENDER systems"

1 - 10 of 11,711 results for
 "RECOMMENDER systems"
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Service-oriented knowledge recommender system and performance evaluation in industrial product development.

Publication Type: Academic Journal

Source(s): International Journal of Production Research. Oct2022, Vol. 60 Issue 20, p6226-6247. 22p. 2 Color Photographs, 10 Diagrams, 7 Charts.

Abstract: Manufacturing firms today co-exist in a complex collaboration network with their partners, who often seek help from external knowledge services to co-develop more competitive products. Thus, knowing how to accurately and rapidly acquire such knowledge ...

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On Sampled Metrics for Item Recommendation.

Publication Type: Periodical

Source(s): Communications of the ACM. Jul2022, Vol. 65 Issue 7, p75-83. 9p. 4 Charts, 4 Graphs.

Abstract: Recommender systems personalize content by recommending items to users. Item recommendation algorithms are evaluated by metrics that compare the positions of truly relevant items among the recommended items. To speed up the computation of metrics, rece...

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When E-Commerce Personalization Systems Show and Tell: Investigating the Relative Persuasive Appeal of Content-Based versus Collaborative Filtering.

Publication Type: Academic Journal

Source(s): Journal of Advertising. Apr/May2022, Vol. 51 Issue 2, p256-267. 12p. 2 Color Photographs, 3 Charts, 1 Graph.

Abstract: In the e-commerce context, are we persuaded more by a product recommendation that matches our preferences (content filtering) or by one that is endorsed by others like us (collaborative filtering)? We addressed this question by conceptualizing these tw...

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HETEROGENEOUS DEMAND EFFECTS OF RECOMMENDATION STRATEGIES IN A MOBILE APPLICATION: EVIDENCE FROM ECONOMETRIC MODELS AND MACHINE-LEARNING INSTRUMENTS.

Publication Type: Academic Journal

Source(s): MIS Quarterly. Mar2022, Vol. 46 Issue 1, p101-150. 50p. 37 Charts, 1 Graph.

Abstract: In this paper, we examine the effectiveness of various recommendation strategies in the mobile channel and their impact on consumers' utility and demand levels for individual products. We find significant differences in effectiveness among various reco...

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Item enhanced graph collaborative network for collaborative filtering recommendation.

Publication Type: Academic Journal

Source(s): Computing. Dec2022, Vol. 104 Issue 12, p2541-2556. 16p.

Abstract: Learning vector embeddings of users and items is the core of modern recommender systems. Recently the collaborative filtering recommender systems based on graph convolutional networks, which integrates the bipartite graph of user-item interaction into ...

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Recommendation system using a deep learning and graph analysis approach.

Publication Type: Academic Journal

Source(s): Computational Intelligence. Oct2022, Vol. 38 Issue 5, p1859-1883. 25p.

Abstract: When a user connects to the Internet to fulfill his needs, he often encounters a huge amount of related information. Recommender systems are the techniques for massively filtering information and offering the items that users find them satisfying and i...

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OPHAencoder: An unsupervised approach to identify groups in group recommendations.

Publication Type: Academic Journal

Source(s): Computing. Dec2022, Vol. 104 Issue 12, p2635-2657. 23p.

Abstract: Recommender systems recommend items to users that would suit the users' preferences. Suggesting personalized items in the context of a group of users is a non-trivial task. The increasing popularity of group recommender systems in recent years attracte...

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Feature-Level Attentive ICF for Recommendation.

Publication Type: Academic Journal

Source(s): ACM Transactions on Information Systems. 2022, Vol. 40 Issue 4, p1-24. 24p.

Abstract: Item-based collaborative filtering (ICF) enjoys the advantages of high recommendation accuracy and ease in online penalization and thus is favored by the industrial recommender systems. ICF recommends items to a target user based on their similarities ...

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Graph Co-Attentive Session-based Recommendation.

Publication Type: Academic Journal

Source(s): ACM Transactions on Information Systems. 2022, Vol. 40 Issue 4, p1-31. 31p.

Abstract: Session-based recommendation aims to generate recommendations merely based on the ongoing session, which is a challenging task. Previous methods mainly focus on modeling the sequential signals or the transition relations between items in the current se...

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Consumption Variety in Food Recommendation.

Publication Type: Academic Journal

Source(s): Journal of the Association for Consumer Research. Oct2022, Vol. 7 Issue 4, p429-437. 9p.

Abstract: This research explores the justification and implications of incorporating consumption variety into mobile-based food recommendation systems. Our study makes use of data from a popular mobile fitness app, in which we can observe large volumes of daily ...

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