This paper describes our novel retrieval model that is based on contexts of query terms in documents (i.e., document contexts). Our model is novel because it explicitly takes into...
Ho Chung Wu, Robert W. P. Luk, Kam-Fai Wong, K. L....
Image databases are nowadays widely exploited in a number of different contexts, ranging from history of art, through medicine, to education. Existing querying paradigms are based ...
Large search engines process thousands of queries per second over billions of documents, making query processing a major performance bottleneck. An important class of optimization...
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...