DocumentCode
2261395
Title
An Intelligent Text Mining System Applied to SEC Documents
Author
Zheng, Ying ; Zhou, Harry
fYear
2012
fDate
May 30 2012-June 1 2012
Firstpage
155
Lastpage
160
Abstract
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.
Keywords
corporate modelling; data mining; information retrieval; knowledge based systems; semantic networks; text analysis; ICGA; SEC EDGAR database; SEC document retrieval; Securities and Exchange Commission; governance characteristics; government agencies; intelligent corporate governance analysis; intelligent text mining system; investors; legislators; local knowledge bases; public companies; rating system; recommended corporate governance practices; semantic networks; Companies; Databases; Industries; Knowledge based systems; Manuals; Semantics; Standards; Semantic net; information retrieval; knowledge base; text mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4673-1536-4
Type
conf
DOI
10.1109/ICIS.2012.124
Filename
6211818
Link To Document