A neural network for discovery of record layouts

Azita Bahrami; Ray R. Hashemi; John R. Talburt; Zhebnya Burachevsky

A neural network for discovery of record layouts

Azita Bahrami, Ray R. Hashemi, John R. Talburt, Zhebnya Burachevsky

Computer Science

Research output: Contribution to book or proceeding › Conference article › peer-review

1 Scopus citations

Abstract

In order for automated systems to interact with ASCII files, they must be able to discover the layout of records. There are three formats of record layouts: fixed, delimited, and mixed. The goal of this paper is to discover the record layout of fixed format. Each record of such files is considered to be a character string in which the fields' startings and endings are unknown and two adjacent fields may or may not be separated by a space. A new neural network was devised to accept a random sample of the file's records as a working set to discover the record layout for the file. The validity of the methodology was established through using 20 different synthesized files with regard to number of fields, length of fields, order of fields, content of fields, or any combination of them. The methodology's ability to discover the record layouts has 95% accuracy.

Original language	English
Title of host publication	Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009
Editors	Patricia Barbosa, Miguel Baptista Nunes, Pedro Isaias, Bebo White, Luis Rodrigues
Publisher	IADIS
Pages	319-323
Number of pages	5
ISBN (Electronic)	9789728924935
State	Published - 2009
Event	IADIS International Conference WWW/Internet 2009, ICWI 2009 - Rome, Italy Duration: Nov 19 2009 → Nov 22 2009

Publication series

Name	Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009
Volume	2

Conference

Conference	IADIS International Conference WWW/Internet 2009, ICWI 2009
Country/Territory	Italy
City	Rome
Period	11/19/09 → 11/22/09

Scopus Subject Areas

Signal Processing
Computer Networks and Communications

Keywords

And record layout discovery
Knowledge discovery
Neural network
Record layout

Cite this

Bahrami, A., Hashemi, R. R., Talburt, J. R., & Burachevsky, Z. (2009). A neural network for discovery of record layouts. In P. Barbosa, M. B. Nunes, P. Isaias, B. White, & L. Rodrigues (Eds.), Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009 (pp. 319-323). (Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009; Vol. 2). IADIS.

Bahrami, Azita ; Hashemi, Ray R. ; Talburt, John R. et al. / A neural network for discovery of record layouts. Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009. editor / Patricia Barbosa ; Miguel Baptista Nunes ; Pedro Isaias ; Bebo White ; Luis Rodrigues. IADIS, 2009. pp. 319-323 (Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009).

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title = "A neural network for discovery of record layouts",

abstract = "In order for automated systems to interact with ASCII files, they must be able to discover the layout of records. There are three formats of record layouts: fixed, delimited, and mixed. The goal of this paper is to discover the record layout of fixed format. Each record of such files is considered to be a character string in which the fields' startings and endings are unknown and two adjacent fields may or may not be separated by a space. A new neural network was devised to accept a random sample of the file's records as a working set to discover the record layout for the file. The validity of the methodology was established through using 20 different synthesized files with regard to number of fields, length of fields, order of fields, content of fields, or any combination of them. The methodology's ability to discover the record layouts has 95% accuracy.",

keywords = "And record layout discovery, Knowledge discovery, Neural network, Record layout",

author = "Azita Bahrami and Hashemi, {Ray R.} and Talburt, {John R.} and Zhebnya Burachevsky",

note = "Publisher Copyright: {\textcopyright} 2009 IADIS.; IADIS International Conference WWW/Internet 2009, ICWI 2009 ; Conference date: 19-11-2009 Through 22-11-2009",

year = "2009",

language = "English",

series = "Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009",

publisher = "IADIS",

pages = "319--323",

editor = "Patricia Barbosa and Nunes, {Miguel Baptista} and Pedro Isaias and Bebo White and Luis Rodrigues",

booktitle = "Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009",

}

Bahrami, A, Hashemi, RR, Talburt, JR & Burachevsky, Z 2009, A neural network for discovery of record layouts. in P Barbosa, MB Nunes, P Isaias, B White & L Rodrigues (eds), Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009. Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009, vol. 2, IADIS, pp. 319-323, IADIS International Conference WWW/Internet 2009, ICWI 2009, Rome, Italy, 11/19/09.

A neural network for discovery of record layouts. / Bahrami, Azita; Hashemi, Ray R.; Talburt, John R. et al.
Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009. ed. / Patricia Barbosa; Miguel Baptista Nunes; Pedro Isaias; Bebo White; Luis Rodrigues. IADIS, 2009. p. 319-323 (Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009; Vol. 2).

Research output: Contribution to book or proceeding › Conference article › peer-review

TY - GEN

T1 - A neural network for discovery of record layouts

AU - Bahrami, Azita

AU - Hashemi, Ray R.

AU - Talburt, John R.

AU - Burachevsky, Zhebnya

PY - 2009

Y1 - 2009

N2 - In order for automated systems to interact with ASCII files, they must be able to discover the layout of records. There are three formats of record layouts: fixed, delimited, and mixed. The goal of this paper is to discover the record layout of fixed format. Each record of such files is considered to be a character string in which the fields' startings and endings are unknown and two adjacent fields may or may not be separated by a space. A new neural network was devised to accept a random sample of the file's records as a working set to discover the record layout for the file. The validity of the methodology was established through using 20 different synthesized files with regard to number of fields, length of fields, order of fields, content of fields, or any combination of them. The methodology's ability to discover the record layouts has 95% accuracy.

AB - In order for automated systems to interact with ASCII files, they must be able to discover the layout of records. There are three formats of record layouts: fixed, delimited, and mixed. The goal of this paper is to discover the record layout of fixed format. Each record of such files is considered to be a character string in which the fields' startings and endings are unknown and two adjacent fields may or may not be separated by a space. A new neural network was devised to accept a random sample of the file's records as a working set to discover the record layout for the file. The validity of the methodology was established through using 20 different synthesized files with regard to number of fields, length of fields, order of fields, content of fields, or any combination of them. The methodology's ability to discover the record layouts has 95% accuracy.

KW - And record layout discovery

KW - Knowledge discovery

KW - Neural network

KW - Record layout

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M3 - Conference article

AN - SCOPUS:84946014262

T3 - Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009

SP - 319

EP - 323

BT - Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009

A2 - Barbosa, Patricia

A2 - Nunes, Miguel Baptista

A2 - Isaias, Pedro

A2 - White, Bebo

A2 - Rodrigues, Luis

PB - IADIS

T2 - IADIS International Conference WWW/Internet 2009, ICWI 2009

Y2 - 19 November 2009 through 22 November 2009

ER -

A neural network for discovery of record layouts

Abstract

Publication series

Conference

Scopus Subject Areas

Keywords

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