An Enhanced Collaborative Filtering-based Approach for Recommender Systems
نویسندگان
چکیده
منابع مشابه
Tag Based Collaborative Filtering for Recommender Systems
Collaborative tagging can help users organize, share and retrieve information in an easy and quick way. For the collaborative tagging information implies user’s important personal preference information, it can be used to recommend personalized items to users. This paper proposes a novel tag-based collaborative filtering approach for recommending personalized items to users of online communitie...
متن کاملEnhanced Collaborative Filtering to Recommender Systems of Technology Enhanced Learning
Recommender Systems (RSs) are largely used nowadays in many areas to generate items of interest to users. Recently, they are applied in the Technology Enhanced Learning (TEL) field to let recommending relevant learning resources to support teachers or learners’ need. In this paper we propose a novel recommendation technique that combines a fuzzy collaborative filtering algorithm with content ba...
متن کاملCollaborative Filtering Recommender Systems
One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of data. In this chapter we introduce the c...
متن کاملCollaborative Filtering Recommender Systems
Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering have led to a varied set of algorithms and a rich collection of tools for evaluating their performance. Research in the field is moving in the d...
متن کاملCollaborative user modeling for enhanced content filtering in recommender systems
Recommender systems, which have emerged in response to the problem of information overload, provide users with recommendations of content suited to their needs. To provide proper recommendations to users, personalized recommender systems require accurate user models of characteristics, preferences and needs. In this study, we propose a collaborative approach to user modeling for enhancing perso...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2020
ISSN: 0975-8887
DOI: 10.5120/ijca2020920531