Identifying and ranking networked biographies and referral paths corresponding to selected qualifications

Abstract

The most common automated search methods produce less-than-ideal results when searching online resumes, profiles, and the like ('biographies') for the identities of people with a searcher-selected qualification ('candidates'). Keywords, their proximities, and their repetitions are less informative in biographies than in other informational documents. Similarly, chains of social connection (“referral paths”) do not always reveal the likelihood or ease of a searcher's introduction to a candidate. In both cases, the display order of results may be unrelated to any estimate of merit. To answer the question “Whom do I need and how do I reach them?” a classifier system uses heuristics or algorithms adapted to match the reactions of human experts on the selected qualifications. Terms in biographies, regardless of structure, are standardized and disambiguated for accurate comparisons, meaningful context is preserved, and biographies and referral paths are scored based on expected usefulness to the searcher.