Extracting Information from Business Documents using Linguistic and Rule-Based System
ORCiD
Leili Javadpour: 0000-0003-4004-1950
Document Type
Conference Presentation
Conference Title
Industrial and Systems Engineering Research Conference (ISERC)
Location
Orlando, FL
Conference Dates
May 19-23, 2012
Date of Presentation
5-1-2012
First Page
2626
Last Page
2631
Abstract
Large amounts of business and engineering knowledge is located in financial and project management reports, business case analysis reports, standard operating procedures, employee hand book, and other types of technical documents which are located outside traditional databases and therefore not easily accessible to database query and mining techniques. There is a growing need for information technologies to extract knowledge from these unstructured data sources. In this study, a corpus of technical documents has been compiled. New algorithms have been developed for automatically extracting domain knowledge from the corpus of technical reports. New methods have been developed for text processing, business rule and taxonomic data extraction from corpus of such reports. For process extraction, rhetorical structure analysis has been used and for concept validation, Wordnet based word sense disambiguation has been used.
Recommended Citation
Halder, A.,
Javadpour, L.,
Khazaeli, M.,
&
Knapp, G. M.
(2012).
Extracting Information from Business Documents using Linguistic and Rule-Based System.
Paper presented at Industrial and Systems Engineering Research Conference (ISERC) in Orlando, FL.
https://scholarlycommons.pacific.edu/esob-facpres/390
