Web content mining for alias identification: A first step towards suspect tracking

In this paper, we present the design of a web content mining system to identify and extract aliases of a given entity from the Web in an automatic way. Starting with a pattern-based information extraction process, the system applies n-gram technique to extract candidate aliases. Thereafter, various statistical measures are applied to identify feasible aliases from them. The extracted aliases can be used to generate profiles of suspects and keep track of their movements on the Web using different identities.