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A text mining system for deviation detection in financial documents

Attempts to mine text documents to discover deviations or anomalies have increased in recent years due to the elevated amount of textual data in today's data repositories. Text mining assists in uncovering hidden information contents across multiple documents.Although various text mining tools...

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Main Authors: Kamaruddin, Siti Sakira, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Mat Nor, Fauzias, Ahmad Nazri, Mohd Zakree, Ali Othman, Zulaiha, Hussein, Ghassan Saleh
Format: Article
Published: IOS Press 2015
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QA76 Computer software
Online Access:http://repo.uum.edu.my/16453/
http://doi.org/10.3233/IDA-150768
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spelling my.uum.repo.164532016-04-27T04:34:00Z http://repo.uum.edu.my/16453/ A text mining system for deviation detection in financial documents Kamaruddin, Siti Sakira Abu Bakar, Azuraliza Hamdan, Abdul Razak Mat Nor, Fauzias Ahmad Nazri, Mohd Zakree Ali Othman, Zulaiha Hussein, Ghassan Saleh QA76 Computer software Attempts to mine text documents to discover deviations or anomalies have increased in recent years due to the elevated amount of textual data in today's data repositories. Text mining assists in uncovering hidden information contents across multiple documents.Although various text mining tools are available, their focus is mainly to assist in data summarization or document classification. These tasks proved to be helpful, however; they do not provide semantic analysis and rigorous textual comparison to detect abnormal sentences that exist in the documents. In this paper, we describe a text mining system that is able to detect sentence deviations from a collection of financial documents.The system implements a dissimilarity function to compare sentences represented as graphs. Our evaluation on the proposed system revolves around experiments using financial statements of a bank. The findings provide valid evidence that the proposed system is able to identify deviating sentences occurring in the documents. The detected deviations can be beneficial for the authorities in order to improve their business decisions. IOS Press 2015 Article PeerReviewed Kamaruddin, Siti Sakira and Abu Bakar, Azuraliza and Hamdan, Abdul Razak and Mat Nor, Fauzias and Ahmad Nazri, Mohd Zakree and Ali Othman, Zulaiha and Hussein, Ghassan Saleh (2015) A text mining system for deviation detection in financial documents. Intelligent Data Analysis, 19 (s1). S19-S44. ISSN 1088467X http://doi.org/10.3233/IDA-150768 doi:10.3233/IDA-150768
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 QA76 Computer software
spellingShingle QA76 Computer software
Kamaruddin, Siti Sakira
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
Mat Nor, Fauzias
Ahmad Nazri, Mohd Zakree
Ali Othman, Zulaiha
Hussein, Ghassan Saleh
A text mining system for deviation detection in financial documents
description Attempts to mine text documents to discover deviations or anomalies have increased in recent years due to the elevated amount of textual data in today's data repositories. Text mining assists in uncovering hidden information contents across multiple documents.Although various text mining tools are available, their focus is mainly to assist in data summarization or document classification. These tasks proved to be helpful, however; they do not provide semantic analysis and rigorous textual comparison to detect abnormal sentences that exist in the documents. In this paper, we describe a text mining system that is able to detect sentence deviations from a collection of financial documents.The system implements a dissimilarity function to compare sentences represented as graphs. Our evaluation on the proposed system revolves around experiments using financial statements of a bank. The findings provide valid evidence that the proposed system is able to identify deviating sentences occurring in the documents. The detected deviations can be beneficial for the authorities in order to improve their business decisions.
format Article
author Kamaruddin, Siti Sakira
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
Mat Nor, Fauzias
Ahmad Nazri, Mohd Zakree
Ali Othman, Zulaiha
Hussein, Ghassan Saleh
author_facet Kamaruddin, Siti Sakira
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
Mat Nor, Fauzias
Ahmad Nazri, Mohd Zakree
Ali Othman, Zulaiha
Hussein, Ghassan Saleh
author_sort Kamaruddin, Siti Sakira
title A text mining system for deviation detection in financial documents
title_short A text mining system for deviation detection in financial documents
title_full A text mining system for deviation detection in financial documents
title_fullStr A text mining system for deviation detection in financial documents
title_full_unstemmed A text mining system for deviation detection in financial documents
title_sort text mining system for deviation detection in financial documents
publisher IOS Press
publishDate 2015
url http://repo.uum.edu.my/16453/
http://doi.org/10.3233/IDA-150768
_version_ 1644281973975285760
score 13.211869

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