Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …

首先根据处理形式的不同, 介绍了不同形式数据的特征和各自的典型应用场景以及相应的代表性
处理系统, 总结了大数据处理系统的三大发展趋势; 随后, 对系统支撑下的大数据分析技术和应用 …

Twitter, Facebook, and other related systems that we call social awareness streams are
rapidly changing the information and communication dynamics of our society. These …

Online news recommender systems aim to address the information explosion of news and
make personalized recommendation for users. In general, news language is highly …

News recommendation is very important to help users find interested news and alleviate
information overload. Different users usually have different interests and the same user may …

Personalized news recommendation is important to help users find their interested news
and improve reading experience. A key problem in news recommendation is learning …

The large number of potential applications from bridging web data with knowledge bases
have led to an increase in the entity linking research. Entity linking is the task to link entity …

Uncovering the topics within short texts, such as tweets and instant messages, has become
an important task for many content analysis applications. However, directly applying …

In a variety of application domains the content to be recommended to users is associated
with text. This includes research papers, movies with associated plot summaries, news …

With the information explosion of news articles, personalized news recommendation has
become important for users to quickly find news that they are interested in. Existing methods …