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Automatic extraction of performance indicators from financial statements

We present a method to automatically analyze financial statements for the purpose of recognizing and extracting relevant financial indicators together with its values and its related narratives.We employ a rule-based approach to solve the problem of syntactical and morphological variations contained...

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Main Authors: Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias
Format: Conference or Workshop Item
Published: 2009
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/15349/
http://doi.org/10.1109/ICEEI.2009.5254714
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spelling my.uum.repo.153492015-09-02T01:38:38Z http://repo.uum.edu.my/15349/ Automatic extraction of performance indicators from financial statements Kamaruddin, Siti Sakira Hamdan, Abdul Razak Abu Bakar, Azuraliza Mat Nor, Fauzias QA75 Electronic computers. Computer science We present a method to automatically analyze financial statements for the purpose of recognizing and extracting relevant financial indicators together with its values and its related narratives.We employ a rule-based approach to solve the problem of syntactical and morphological variations contained within the financial text.The information was extracted using a multi-pass scan to process the text in a series of pre-programmed functions. Experiments were carried out to demonstrate the feasibility of the system by deriving the precision and recall scores.The extracted results can be used to construct and augment knowledge bases for a more complex text mining systems. 2009 Conference or Workshop Item PeerReviewed Kamaruddin, Siti Sakira and Hamdan, Abdul Razak and Abu Bakar, Azuraliza and Mat Nor, Fauzias (2009) Automatic extraction of performance indicators from financial statements. In: International Conference on Electrical Engineering and Informatics, 2009 (ICEEI '09), 5-7 Aug. 2009, Selangor. http://doi.org/10.1109/ICEEI.2009.5254714 doi:10.1109/ICEEI.2009.5254714
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Kamaruddin, Siti Sakira
Hamdan, Abdul Razak
Abu Bakar, Azuraliza
Mat Nor, Fauzias
Automatic extraction of performance indicators from financial statements
description We present a method to automatically analyze financial statements for the purpose of recognizing and extracting relevant financial indicators together with its values and its related narratives.We employ a rule-based approach to solve the problem of syntactical and morphological variations contained within the financial text.The information was extracted using a multi-pass scan to process the text in a series of pre-programmed functions. Experiments were carried out to demonstrate the feasibility of the system by deriving the precision and recall scores.The extracted results can be used to construct and augment knowledge bases for a more complex text mining systems.
format Conference or Workshop Item
author Kamaruddin, Siti Sakira
Hamdan, Abdul Razak
Abu Bakar, Azuraliza
Mat Nor, Fauzias
author_facet Kamaruddin, Siti Sakira
Hamdan, Abdul Razak
Abu Bakar, Azuraliza
Mat Nor, Fauzias
author_sort Kamaruddin, Siti Sakira
title Automatic extraction of performance indicators from financial statements
title_short Automatic extraction of performance indicators from financial statements
title_full Automatic extraction of performance indicators from financial statements
title_fullStr Automatic extraction of performance indicators from financial statements
title_full_unstemmed Automatic extraction of performance indicators from financial statements
title_sort automatic extraction of performance indicators from financial statements
publishDate 2009
url http://repo.uum.edu.my/15349/
http://doi.org/10.1109/ICEEI.2009.5254714
_version_ 1644281695517540352
score 13.211869

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