Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues arise from many disciplines such as information retrieval, data-mining, machine learning and computer vision. Despite continuous efforts have been taken in the last several decades, these two issues remain challenging. They become more and more imminent given the big data emerges in various fields and h...

L1 graph is an effective way to represent data samples in many graph-oriented machine learning applications. Its original construction algorithm is nonparametric, and the graphs it generates may have high sparsity. Meanwhile, the construction algorithm also requires many iterative convex optimization calculations and is very time-consuming. Such characteristics would severely limit the applicat...

Call graph construction has been an important area of research within the compilers and programming languages community. However, all existing techniques focus on exhaustive analysis of all the call-sites in the program. With increasing importance of just-in-time or dynamic compilation and use of program analysis as part of the software development environments, we believe that there is a need ...

Graph abstraction is essential for many applications, from finding a shortest path to executing complex machine learning (ML) algorithms like collaborative filtering. However, constructing graphs from relationships hidden within large unstructured datasets is challenging. Since graph construction is a data-parallel problem, MapReduce is well-suited for this task. We developed GraphBuilder, an o...

Rough membership function defines the degree of relationship between conditional and decision attributes an information system. It is defined by where src=image/13429145_07.gif> subset src=image/13429145_08.gif> under relation src=image/13429145_09.gif> universe discourse. can be expressed in different forms like cardinality form, probabilistic form etc. In it as...

Automatic knowledge graph construction aims to manufacture structured human knowledge. To this end, much effort has historically been spent extracting informative fact patterns from different data sources. However, more recently, research interest shifted acquiring conceptualized beyond data. In addition, researchers have also exploring new ways of handling sophisticated tasks in diversified sc...