The recommender systems are recently becoming more significant in the age of rapid
development of the Internet technology due to their ability in making a decision to users on …

Link prediction is an important task in data mining, which has widespread applications in
social network research. Given a social network, the objective of this task is to predict future …

Recommender systems have been regarded as gaining a more significant role with the
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …

Medical information retrieval plays an increasingly important role to help physicians and
domain experts to better access medical-related knowledge and information, and support …

Predicting and Identifying behavioral analysis in social media using big data analytics is
exceptionally repetitive. Since data in motion are difficult to capture and process with …

Analyzing “what topics” a user discusses with others is important in social network analysis.
Since social relationships can be represented as multiobject relationships (eg, those …

Response selection is a critical issue in the AI community, with important applications on the
Web. The accuracy of the selected responses, however, tends to be insufficient due to the …

Tensor completion originates in numerous applications where data utilized are of high
dimensions and gathered from multiple sources or views. Existing methods merely …

Social tagging systems (STSs) allow collaborative users to share and annotate many types
of resources with descriptive and semantically meaningful information in freely chosen text …

K-means algorithm is one of the most influential clustering algorithms in the field of data
mining. It is widely used in many fields, such as school, daily consumption, transfer, and …