Intelligent tourism recommender systems: A survey
Recommender systems are currently being applied in many different domains. This paper
focuses on their application in tourism. A comprehensive and thorough search of the smart e …
focuses on their application in tourism. A comprehensive and thorough search of the smart e …
Social recommendation: a review
Recommender systems play an important role in helping online users find relevant
information by suggesting information of potential interest to them. Due to the potential value …
information by suggesting information of potential interest to them. Due to the potential value …
A survey of collaborative filtering based social recommender systems
Recommendation plays an increasingly important role in our daily lives. Recommender
systems automatically suggest to a user items that might be of interest to her. Recent studies …
systems automatically suggest to a user items that might be of interest to her. Recent studies …
From zero-shot learning to cold-start recommendation
Zero-shot learning (ZSL) and cold-start recommendation (CSR) are two challenging
problems in computer vision and recommender system, respectively. In general, they are …
problems in computer vision and recommender system, respectively. In general, they are …
Improving user topic interest profiles by behavior factorization
Many recommenders aim to provide relevant recommendations to users by building
personal topic interest profiles and then using these profiles to find interesting contents for …
personal topic interest profiles and then using these profiles to find interesting contents for …
Recommender systems in industry: A netflix case study
X Amatriain, J Basilico - Recommender systems handbook, 2015 - Springer
Recommender Systems are a prime example of the mainstream industry use of large-scale
machine learning and data mining. Diverse applications in areas such as e-commerce …
machine learning and data mining. Diverse applications in areas such as e-commerce …
Social recommendation with cross-domain transferable knowledge
Recommender systems can suffer from data sparsity and cold start issues. However, social
networks, which enable users to build relationships and create different types of items …
networks, which enable users to build relationships and create different types of items …
Mining large streams of user data for personalized recommendations
X Amatriain - ACM SIGKDD Explorations Newsletter, 2013 - dl.acm.org
The Netflix Prize put the spotlight on the use of data mining and machine learning methods
for predicting user preferences. Many lessons came out of the competition. But since then …
for predicting user preferences. Many lessons came out of the competition. But since then …
Cold-start recommendation using bi-clustering and fusion for large-scale social recommender systems
Social recommender systems leverage collaborative filtering (CF) to serve users with
content that is of potential interesting to active users. A wide spectrum of CF schemes has …
content that is of potential interesting to active users. A wide spectrum of CF schemes has …