An ongoing project explores the extent to which artificial intelligence (AI), specifically in the
areas of natural language processing and semantic reasoning, can be exploited to facilitate …

In this paper, we study the problem of author identification under double-blind review setting,
which is to identify potential authors given information of an anonymized paper. Different …

In this paper, we study the problem of author identification in big scholarly data, which is to
effectively rank potential authors for each anonymous paper by using historical data. Most of …

The objective of entity resolution (ER) is to identify records referring to the same real-world
entity. Traditional ER approaches identify records based on pairwise similarity comparisons …

Many real-world tasks solved by heterogeneous network embedding methods can be cast
as modeling the likelihood of a pairwise relationship between two nodes. For example, the …

The digital repository of research articles is increasing at a rapid rate and hence searching
the right paper becoming a tedious task for researchers. A research paper recommendation …

The tremendous advances in computer science in the last few decades have provided the
platform to address and solve complex problems using interdisciplinary research. In this …

We study the problem of author-paper correlation inference in big scholarly data, which is to
effectively infer potential correlated works for researchers using historical records. Unlike …

Relation learning, widely used in recommendation systems or relevant entity search over
knowledge graphs, has attracted increasing attentions in recent years. Existing methods like …

Web personalization, eg, recommendation or relevance search, tailoring a service/product to
accommodate specific online users, is becoming increasingly important. Inductive …