Recommender system has been one of the main enabler of eCommerce personalization, and there have been many researches for improving the fitness of recommendation. However, the necessity of aggregated personal information has pointed out the privacy risk of recommender system. In this paper, we provide basic framework for analyzing the behavior of private information sharing in recommender syste...

This paper shows how image content can be used to realize a shopping recommender system for intuitively supporting mobile users in decision making. A mobile user equipped with a camera enabled smart phone combined with Global Positioning System (GPS) capabilities would benefit in using a recommender system for mobile users. This recommender system is queried by image sent by a smart phone toget...

WHO estimates that the number of people with diabetes will grow 114% by 2030.It declares that, patients have to play a major role to control and therapy of diabetes by being provided with updated knowledge about the disease and different aspects of available treatments, diet therapy in particular. In this regard, diets recommender Systems would be helpful. They are techniques and tools which su...

In general, the study of recommender systems emphasizes the efficiency of techniques to provide accurate recommendations rather than factors influencing users’ acceptance of the system; however, accuracy alone cannot account for users’ satisfying experience. Bearing in mind this gap in the research, we apply the technology acceptance model (TAM) to evaluate user acceptance of a recommender syst...

Recommender systems have become a popular technique and strategy for helping users select desirable products or services. Most research in this area focused on applying the method to help the customers in Business-to-Customer (B2C) electronic commerce (e-commerce), however, the participants in Businessto-Business (B2B) market can also get useful assistance from the recommender system. In this a...

Recommender System are new generation internet tool that help user in navigating through information on the internet and receive information related to their preferences. Although most of the time recommender systems are applied in the area of online shopping and entertainment domains like movie and music, yet their applicability is being researched upon in other area as well. This paper presen...

With the fleetly development of the internet, discovering useful knowledge from the World Wide Web became a censorious issue. With the huge volume of information present in the internet, user needs a help via recommendation system. From the user’s log data lot of recommender systems developed to predict the user’s next request when they view the web pages. However, each recommender system has i...

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...

Recommender systems that inform consumers about their likely ideal product have become the cornerstone of eCommerce platforms that sell products from competing manufacturers. Using a model of an electronic marketplace in which two competing manufacturers produce substitutable products and sell the products through a common retail platform, we study the e ect of recommender systems on the market...

One of the anticipated challenges of today’s e-learning is to solve the problem of recommending from a large number of learning materials. In this study, we introduce a novel architecture for an e-learning recommender system. More specifically, this paper comprises the following phases i) to propose an e-learning recommender system based on content-based filtering and good learners’ ratings, an...