Category-based data analysis system for processing stored data-units and calculating their relevance to a subject domain with exemplary precision, and a computer-implemented method for identifying from a broad range of data sources, social entities that perform the function of Social Influencers

摘要

A category-based data analysis system for processing stored data-units and calculating their relevance to a subject domain with exemplary precision over Web and electronic document searches. A central processor parses a search definition comprising queries against target data sources, and a Boolean expression before launching a plurality of search engines. The Boolean expression and subexpressions comprise individual key-phrases and categories of key-phrases. Fine control of natural language matching behavior is controlled by parameters at the category and key-phrase level. The search engine reads data-units from a plurality of data sources, evaluates relevance, and stores metadata with the data-unit comprising relevance data by key-phrase and category. These results can be further analyzed by SQL query engines, spreadsheets, and Business Intelligence tools.;A computer-implemented method for identifying from a broad range of data sources, social entities that perform the function of Social Influencers. The method aggregates relevant results to provide a more comprehensive analysis of a subject domain than can be achieved with a manual search. Search results are presented in the form of web-presences that are logically related webpages, disaggregated and categorized from websites. Web-presences can be clustered by association with a social entity and are ranked to determine their function as Social Influencers. These results can be further analyzed by SQL query engines, spreadsheets, and Business Intelligence tools.