PERSON DISAMBIGUATION USING NAME ENTITY EXTRACTION-BASED CLUSTERING

Described is a technology for disambiguating data corresponding to persons that are located from search results, so that different persons having the same name can be clearly distinguished. Name entity extraction locates words (terms) that are within a certain distance of persons' names in the search results. The terms are used in disambiguating search results that correspond to different persons having the same name, such as location information, organization information, career information, and/or partner information. In one example, each person is represented as a vector, and similarity among vectors is calculated based on weighting that corresponds to nearness of the terms to a person, and/or the types of terms. Based on the similarity data, the person vectors that represent the same person are then merged into one cluster, so that each cluster represents (to a high probability) only one distinct person.