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Recommender systems, inferring users' preferences from their historical activities and personal profiles, have been an enormous success in the last several years. Most of the existing works are based on the similarities of users, objects or both that derived from their purchases records in the online shopping platforms. Such approaches, however, are facing bottlenecks when the known information is...
The recommender system can partially alleviate user's difficulty on information filtering and discover valuable information for the active user. Collaborative filtering has been widely used for recommendation. Because of facing the large-scale and sparse user-item rating matrix, high precision and better performance are always the big challenges for recommender system. In this paper, we model the...
Retrieving items in online e-commerce systems with abundance of products is time consuming for users. To deal with this issue, recommender systems (RS) aims to help users by suggesting their interested items in the presence of thousands of products. Generally, RS algorithms are constructed based on similarity between users and/or items (e.g., a user is likely to purchase the same items as his/her...
The majority of existing recommender systems use one or more statistical techniques to recommend content. While such techniques can be very effective, they have a number of restrictions, such as their inability to recommend items based on meaning or relationships between different characteristics of each item. This paper describes the design of a hybrid recommender system that uses a combination of...
Tag recommendation is an integral part of any bookmarking application. With the growing popularity in Web 2.0 usage, recommending tags is of utmost importance in enabling a user to perform bookmarking easily. An issue that most recommendation systems do not consider is that users have a tendency to choose from tags that are suggested to them, which might bias the true popular rankings of tags. In...
Recommender systems have emerged as an essential response to the rapidly growing digital information phenomenon in which users are finding it more and more difficult to locate the right information at the right time. Systems under Web2.0 allow users not only to give resources- ratings but also to assign tags to them. Tags play a significant role in Web 2.0. They can be used for navigation, browsing,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.