Benefiting from the powerful expressive capability of graphs, graph-based approaches have
been popularly applied to handle multi-modal medical data and achieved impressive …

Distributional semantic models derive computational representations of word meaning from
the patterns of co-occurrence of words in text. Such models have been a success story of …

The problem of joint modeling the text and image components of multimedia documents is
studied. The text component is represented as a sample from a hidden topic model, learned …

The problem of cross-modal retrieval from multimedia repositories is considered. This
problem addresses the design of retrieval systems that support queries across content …

Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of
medical image data are captured and recorded in a digital format during cancer care and …

This paper addresses the challenge of Multimedia Event Detection by proposing a novel
method for high-level and low-level features fusion based on collective classification …

Cross media retrieval systems have received increasing interest in recent years. Due to the
semantic gap between low-level features and high-level semantic concepts of multimedia …

In recent years, multimedia retrieval has sparked much research interest in the multimedia,
pattern recognition, and data mining communities. Although some attempts have been made …

Cross-media analysis exploits social data with different modalities from multiple sources
simultaneously and synergistically to discover knowledge and better understand the world …

With the advent of various services and applications of Semantic Web, semantic annotation
has emerged as an important research topic. The application of semantically annotated …