Abstract—Comparing graphs to determine the level of underlying structural similarity between them is a widely encountered problem in computer science. It is particularly relevant...
Damien Fay, Hamed Haddadi, Andrew Thomason, Andrew...
Clustering on multi-type relational data has attracted more and more attention in recent years due to its high impact on various important applications, such as Web mining, e-comm...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
This paper addresses the problem of learning similaritypreserving binary codes for efficient retrieval in large-scale image collections. We propose a simple and efficient altern...
The Generalized Local Discriminant Bases (GLDB) algorithm proposed by Kumar, Ghosh and Crawford in [4], is a effective feature extraction method for spectral data. It identifies g...