Constraint-based recommendation systems are used in many different domains like notebooks, cars, and mobile phones. Such systems describe product domains in sets of product and customer variables, their domains, and constraints which define the relationship between the variables. Maintenance is a crucial task in constraint-based recommendation systems, because it is timeconsuming and error-pron...

The Knowledge discovery tools and techniques are used in an increasing number of scientific and commercial areas for the analysis and knowledge processing of voluminous Information. Recommendation systems are also one of Knowledge Discovery from databases techniques, which discovers best fit information for appropriate context. This new rage in Information technology is seen in area of E-commer...

Online Social Networks (OSNs) have grown a lot from the past and now it is becoming more and more popular in today’s life. The main problem facing by today’s networks is “information overloading”. A solution to this problem is a good recommendation system. It automatically suggests items to a user that he/she is having interest in it. To improve the accuracy and precision of recommendation syst...

Web-based recommendation systems are becoming increasingly popular. Systems ranging from those like Siteseer that use user’s bookmarks as surrogates for preferences to those that provide content-based and collaborative recommendations are gaining user’s attention. This study proposes a validated instrument to measure such constructs as perceived usefulness, perceived ease of use, perceived cont...

Recommendation systems have been growing in number for the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth...

World Wide Web is the biggest source of information. Though the World Wide Web contains a tremendous amount of data, most of the data is irrelevant and inaccurate from users’ point of view. Consequently it has become increasingly necessary for users to utilize automated tools such as recommender systems in order to discover, extract, filter, and evaluate the desired information and resources. M...

In recommendation systems, service providers can recommend products to their customers based on personal data from many users. To avoid leakage of these personal data, service providers use secret sharing. This enables them to compute the recommendation, while remaining oblivious to the contents. Only the user requesting the output will be able to combine all shares of the recommendation and le...

The increasingly complicated workflow systems necessitates the development of automated workflow recommendation techniques, which are able to not only speed up the workflow construction process, but also reduce the errors that are possibly made. The existing workflow recommendation systems are quite limited in that they cannot produce a correct recommendation of the next node if the upstream no...

As the World Wide Web becomes a large source of digital music, the music recommendation system has got a great demand. There are several music recommendation systems for both commercial and academic areas, which deal with the user preference as fixed. However, since the music preferred by a user may change depending on the contexts, the conventional systems have inherent problems. This paper pr...