An Intelligent Text Mining System Applied to SEC Documents

Computer and Information Science（2012）

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摘要

This paper presents an intelligent corporate governance analysis and rating system, called ICGA, capable of retrieving SEC required documents of public companies and performing analysis and rating in terms of recommended corporate governance practices. With local knowledge bases, databases, and semantic networks, ICGA is able to automatically evaluate the strengths, deficiencies, and risks of a company's corporate governance practices and board of directors based on the documents stored in the SEC EDGAR database. The produced score reduces a complex corporate governance process and related policies into a single number which enables concerned government agencies, investors and legislators to assess the governance characteristics of individual companies.

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关键词

icga,sec documents,governance characteristic,government agencies,knowledge based systems,knowledge base,semantic networks,recommended corporate governance practices,intelligent text mining system,information retrieval,sec edgar database,sec document retrieval,governance characteristics,corporate governance practice,complex corporate governance process,intelligent corporate governance analysis,legislators,recommended corporate governance practice,corporate modelling,individual company,local knowledge bases,data mining,semantic net,rating system,concerned government agency,securities and exchange commission,public companies,text analysis,investors,retrieving sec,text mining,knowledge based system,semantic network,semantics,databases,local knowledge,corporate governance

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