1. Introduction Recommender systems provide advice to users about items they might wish to purchase or examine. Recommendations made by such systems can help users navigate through large information spaces of product descriptions, news articles or other items. As on-line information and e-commerce burgeon, recommender systems are an increasingly important tool. A recent survey of recommender sy...

In the era of Internet, web is a giant source of information. The constantly growing rate of information in the web makes people confused to decide which product is relevant to them. To find relevant product in today’s era is very time consuming and tedious task. Everyday a lot of information is uploaded and retrieved from the web. The web is overloaded with information and it is very essential...

The implementation of recommender systems in electronic procurement processes for service packages, consisting of productand service components requires a consideration of strategic, tactical and operational procurement as well as information and communication technologies in value networks. Increasingly, the design of recommender systems for procurement processes in value networks is of scient...

Recommender Systems are effective methods that have been developed successfully in e-commerce to provide personal recommendations based on user’s previous preferences. A recommender system assists users in a decision-making process to suggest interesting items from overwhelming flood of data available in the system. Suitably adapting the technology, recommender systems for medical purposes have...

The issue of trust is important in recommender systems. These systems are typically described in terms of perceived reliability of the recommender coupled with a content quality perspective. However, most studies do not address the complete user context and psychological environment of a recommender system. This environment and context are described here by three primary areas of consideration,...

We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called “recommender systems”. Recommender systems apply knowledge discovery techniques to the problem of making product recommendations during a live customer interaction. These systems are achieving widespread success in E-commerce nowadays, especially with the advent of the Inte...

It is difficult to deny that comparison between recommender systems requires a common way for evaluating them. Nevertheless, at present, they have been evaluated in many, often incompatible, ways. We affirm this problem is mainly due to the lack of a common framework for recommender systems, a framework general enough so that we may include the whole range of recommender systems to date, but sp...

1 Introduction Recommender systems offer benefits to both consumers and firms. For consumers, recommender systems help individuals both become aware of new products as well as select desirable products among myriad choices (Pham & Healey, 2005). For firms, recommender systems have the potential to increase profits by converting browsers into buyers, cross-selling products, and increasing loyalt...

BACKGROUND What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior t...