Document clustering on target entities using persons and organizations

Abstract

Web surfing often involves carrying out information finding tasks using online search engines. These searches often contain keywords that are names, as in the case of Persons and Organizations (abbreviated a??PnOsa??). Such names are often not distinctive, commonly occurring, and non-unique. Thus, a single name may be mapped to several named entities. The result is users having to sift through mountains of pages and put together manually a set of information pertaining to the target entity in query.