Recommender systems: Techniques, applications, and challenges
Recommender systems (RSs) are software tools and techniques that provide suggestions
for items that are most likely of interest to a particular user. In this introductory chapter, we …
for items that are most likely of interest to a particular user. In this introductory chapter, we …
Recommender system application developments: a survey
A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …
recommendations to handle the increasing online information overload problem and …
Introduction to recommender systems handbook
Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions for items to be of use to a user. In this introductory chapter we briefly discuss …
suggestions for items to be of use to a user. In this introductory chapter we briefly discuss …
Social network and tag sources based augmenting collaborative recommender system
Recommender systems, which provide users with recommendations of content suited to
their needs, have received great attention in today's online business world. However, most …
their needs, have received great attention in today's online business world. However, most …
A reliability-based recommendation method to improve trust-aware recommender systems
P Moradi, S Ahmadian - Expert Systems with Applications, 2015 - Elsevier
Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …
make personalized recommendations for user's information on the web. In online sharing …
A matrix factorization based dynamic granularity recommendation with three-way decisions
D Liu, X Ye - Knowledge-Based Systems, 2020 - Elsevier
Recommender systems (RSs) are effective technologies and tools used to deal with the
problems of information overload, and have been developed rapidly in nearly two decades …
problems of information overload, and have been developed rapidly in nearly two decades …
Facebook single and cross domain data for recommendation systems
The emergence of social networks and the vast amount of data that they contain about their
users make them a valuable source for personal information about users for recommender …
users make them a valuable source for personal information about users for recommender …
EventAction: Visual analytics for temporal event sequence recommendation
Recommender systems are being widely used to assist people in making decisions, for
example, recommending films to watch or books to buy. Despite its ubiquity, the problem of …
example, recommending films to watch or books to buy. Despite its ubiquity, the problem of …
An entropy-based neighbor selection approach for collaborative filtering
C Kaleli - Knowledge-Based Systems, 2014 - Elsevier
Collaborative filtering is an emerging technology to deal with information overload problem
guiding customers by offering recommendations on products of possible interest. Forming …
guiding customers by offering recommendations on products of possible interest. Forming …
[图书][B] Proactive data mining using decision trees
In the previous chapter we introduced the task of proactive data mining and sketched an
algorithmic framework for solving the task: first build a prediction model and then use it for …
algorithmic framework for solving the task: first build a prediction model and then use it for …