the evaluation and selection of recommender systems is a difficult decision making process. this difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. as such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...

The rapid development of technology, the Internet, and the development of electronic commerce have led to the emergence of recommender systems. These systems will assist the users in finding and selecting their desired items. The accuracy of the advice in recommender systems is one of the main challenges of these systems. Regarding the fuzzy systems capabilities in determining the borders of us...

Location and its corollary, distance, are critical concepts in social computing. Recommender systems that incorporate location have generally assumed that the utility of locationawareness monotonically decreases as entities get farther apart. However, it is well known in geography that places that are distant “as the crow flies” can be more similar and connected than nearby places (e.g., by dem...

Recently, recommender systems have been widely used in e-commerce websites to help customers discover items they want. Since a recommender system should be able to provide users with helpful information regarding items that might interest them, the ability to immediately respond to changes in a user’s preference is a valuable asset of the systems. Thus, this work presents a novel recommender sy...

cold start is one of the main challenges in recommender systems. solving sparsechallenge of cold start users is hard. more cold start users and items are new. sine many general methods for recommender systems has over fittingon cold start users and items, so recommendation to new users and items is important and hard duty. in this work to overcome sparse problem, we present a new method for rec...

With the rapid expansion of the information on the Internet, recommender systems play an important role in terms of trade and research. Recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. In the past dec...

with the rapid expansion of the information on the internet, recommender systems play an important role in terms of trade and research. recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. ...