Results 1 - 10
of
17,512
Analysis of Recommendation Algorithms for E-Commerce
, 2000
"... Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in E-Commerce nowadays. In this paper, we investigate several techniques for analyzing large-scale pu ..."
Abstract
-
Cited by 523 (22 self)
- Add to MetaCart
Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in E-Commerce nowadays. In this paper, we investigate several techniques for analyzing large
MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS
- IEEE COMPUTER
, 2009
"... As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels. Modern co ..."
Abstract
-
Cited by 593 (4 self)
- Add to MetaCart
As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels. Modern
Personalization of Supermarket Production Recommendations
- Data Mining and Knowledge Discovery
, 2000
"... We describe a personalized recommender system designed to suggest new products to supermarket shoppers. The recommender functions in a pervasive computing environment, namely, a remote shopping system in which supermarket customers use Personal Digital Assistants (PDAs) to compose and transmit their ..."
Abstract
-
Cited by 46 (0 self)
- Add to MetaCart
We describe a personalized recommender system designed to suggest new products to supermarket shoppers. The recommender functions in a pervasive computing environment, namely, a remote shopping system in which supermarket customers use Personal Digital Assistants (PDAs) to compose and transmit
The Developing of Customer Product Recommendation
"... In recent years, the styles and functions of products have become very diverse due to the rapid advancement of new technologies. Before, customers were finding it hard to decide on what they would need although they have more product knowledge and choices. They were often unable to articulate their ..."
Abstract
- Add to MetaCart
be offered to customers. To this end, this study undertakes to build a customized product recommendation service system that parameterizes customer needs and product features, using the information axiom and the Taguchi method to create the system’s search and evaluation function. In addition, the triangular
Using Taxonomies for Product Recommendation
"... Abstract. In this work we take advantage of valuable information encoded in taxonomies to improve the quality of recommender systems. We present three strategies that explore the use of taxonomies: (i) category descriptors, (ii) classification features and (iii) category filters. We provide a real-c ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
Abstract. In this work we take advantage of valuable information encoded in taxonomies to improve the quality of recommender systems. We present three strategies that explore the use of taxonomies: (i) category descriptors, (ii) classification features and (iii) category filters. We provide a real
Product Recommender Systems
, 2008
"... et de nationalité chinoise acceptée sur proposition du jury: ..."
Product recommendation systems: A new direction
- in ‘Proceedings of the Workshop Programme at the Fourth International Conference on Case-Based Reasoning
, 2001
"... This paper is about content-based product recommender systems. In product recommendation, a customer is presented with a selection of products from a product catalogue. Content-based approaches (in contradistinction to, ..."
Abstract
-
Cited by 21 (1 self)
- Add to MetaCart
This paper is about content-based product recommender systems. In product recommendation, a customer is presented with a selection of products from a product catalogue. Content-based approaches (in contradistinction to,
Automatic home medical product recommendation
- JMS
"... Abstract Web-based personal health records (PHRs) are being widely deployed. To improve PHR’s capability and usability, we proposed the concept of intelligent PHR (iPHR). In this paper, we use automatic home medical product recommendation as a concrete application to demonstrate the benefits of intr ..."
Abstract
-
Cited by 9 (8 self)
- Add to MetaCart
Abstract Web-based personal health records (PHRs) are being widely deployed. To improve PHR’s capability and usability, we proposed the concept of intelligent PHR (iPHR). In this paper, we use automatic home medical product recommendation as a concrete application to demonstrate the benefits
Product Recommendation Systems: A New Direction
"... This paper is about content-based product recommender systems. In product recommendation, a customer is presented with a selection of products from a product catalogue. Content-based approaches (in contradistinction to, ..."
Abstract
- Add to MetaCart
This paper is about content-based product recommender systems. In product recommendation, a customer is presented with a selection of products from a product catalogue. Content-based approaches (in contradistinction to,
Social Commerce Hybrid Product Recommender
"... The vision for Web 3.0 (also known as Semantic Web) is the ability to create meaning out of huge quantity of qualitative data. Existing data can be interconnected for further uses. Web 2.0 focused on the users interaction with others whereas Web 3.0 focus more on the users themselves. The advantages ..."
Abstract
- Add to MetaCart
. Then the related literature work regarding hybrid recommenders is discussed. Next it is discussed how to predict ratings from a user-item rating network and friend’s network and then how to unify similarity matrices obtained from different networks. And lastly this paper covers the social hybrid product
Results 1 - 10
of
17,512