—Ranking plays important roles in contemporary Internet and vertical search engines. Among existing ranking algorithms, link analysis based algorithms have been proved as effecti...
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. The tradi...
We describe an approach for multi-modal characterization of social media by combining text features (e.g. tags as a prominent example of short, unstructured text labels) with spat...