Personalized PageRank (PPR) has been successfully applied to various applications. In
real applications, it is important to set PPR parameters in an ad-hoc manner when finding …

For the AI community, the lasso proposed by Tibshirani is an important regression approach
in finding explanatory predictors in high dimensional data. The coordinate descent algorithm …

Discovering user similarities from social media can establish the basis for user targeting,
product recommendation, user relationship evolution and understanding. User similarities …

The ability to predict the activities of users is an important one for recommender systems and
analyses of social media. User activities can be represented in terms of relationships …

Subjective assessments (SAs), such as “elegant” and “gorgeous,” are assigned to items by
users, and they are common in the reviews and tags found on many online sites. Analyzing …

Tracking user interests over time is important for making accurate recommendations.
However, the widely-used time-decay-based approach worsens the sparsity problem …

We propose a probabilistic topic model that infers the relevance of contentdescriptive
metadata to assist in the task of collaborative filtering. Metadata can be used to add …

抄録 Tracking user interests over time is important for making accurate recommendations.
However, the widely-used time-decay-based approach worsens the sparsity problem …

抄録 Content providers want to make recommendations across multiple interrelated domains
such as music and movies. However, existing collaborative filtering methods fail to …

抄録 Predicting human activities is important for improving recommender systems or
analyzing social relationships among users. Those human activities are usually represented …