Identification of all objects in a dataset whose similarity is not less than a specified threshold is of major importance for management, search, and analysis of data. Set similari...
Abstract-- We study the convergence rate of average consensus algorithms in networks with stochastic communication failures. We show how the system dynamics can be modeled by a dis...
Semantic relatedness between words is important to many NLP tasks, and numerous measures exist which use a variety of resources. Thus far, such work is confined to measuring simil...
We present an approach to the discovery of semantically similar terms that utilizes a web search engine as both a source for generating related terms and a tool for estimating the...
We present a simple linguistically-motivated method for characterizing the semantic relations that hold between two nouns. The approach leverages the vast size of the Web in order...