Why I like it: multi-task learning for recommendation and explanation
We describe a novel, multi-task recommendation model, which jointly learns to perform
rating prediction and recommendation explanation by combining matrix factorization, for …
rating prediction and recommendation explanation by combining matrix factorization, for …
Temporal people-to-people recommendation on social networks with sentiment-based matrix factorization
Nowadays, the exponential advancement of social networks is creating new application
areas for recommender systems (RSs). People-to-people RSs aim to exploit user's interests …
areas for recommender systems (RSs). People-to-people RSs aim to exploit user's interests …
Enhancing structural diversity in social networks by recommending weak ties
J Sanz-Cruzado, P Castells - Proceedings of the 12th ACM conference …, 2018 - dl.acm.org
Contact recommendation has become a common functionality in online social platforms, and
an established research topic in the social networks and recommender systems fields …
an established research topic in the social networks and recommender systems fields …
Improving user recommendation by extracting social topics and interest topics of users in uni-directional social networks
With the rapid growth of population on social networks, people are confronted with
information overload problem. This clearly makes filtering the targeted users a demanding …
information overload problem. This clearly makes filtering the targeted users a demanding …
Tweet and followee personalized recommendations based on knowledge graphs
Twitter users get the latest tweets of their followees on their timeline. However, they are often
overwhelmed by the large number of tweets, which makes it difficult for them to find …
overwhelmed by the large number of tweets, which makes it difficult for them to find …
People recommendation on social media
I Guy - Social information access: Systems and technologies, 2018 - Springer
The social web has brought about many new types of recommender systems. One of the
most important is recommendation of people, which bears many unique characteristics and …
most important is recommendation of people, which bears many unique characteristics and …
Dual implicit mining-based latent friend recommendation
The latent friend recommendation in online social media is interesting, yet challenging,
because the user-item ratings and the user-user relationships are both sparse. In this paper …
because the user-item ratings and the user-user relationships are both sparse. In this paper …
3-HBP: A three-level hidden Bayesian link prediction model in social networks
In social networks, link establishment among the users is affected by complex factors. In this
paper, we try to investigate the internal and external factors that affect the formation of links …
paper, we try to investigate the internal and external factors that affect the formation of links …
Behavioral data mining to produce novel and serendipitous friend recommendations in a social bookmarking system
In the last few years, social media systems have experienced a fast growth. The amount of
content shared in these systems increases fast, leading users to face the well known …
content shared in these systems increases fast, leading users to face the well known …
Lost in migration: Information management and community building in an online health community
D Nakikj, L Mamykina - Proceedings of the 2018 CHI Conference on …, 2018 - dl.acm.org
The ever-growing volume of information within online health communities (OHCs) presents
an urgent need for new solutions that improve the efficiency of information organization and …
an urgent need for new solutions that improve the efficiency of information organization and …