TEXUS: table extraction system for PDF documents

Roya Rastan; Hye Young Paik; John Shepherd; Seung Hwan Ryu; Amin Beheshti

doi:10.1007/978-3-319-92013-9_30

TEXUS

table extraction system for PDF documents

Roya Rastan, Hye Young Paik, John Shepherd, Seung Hwan Ryu^*, Amin Beheshti

^*Corresponding author for this work

Department of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

5 Citations (Scopus)

Abstract

Tables in documents are a rich and under-exploited source of structured data in otherwise unstructured documents. The extraction and understanding of tabular data is a challenging task which has attracted the attention of researchers from a range of disciplines such as information retrieval, machine learning and natural language processing. In this demonstration, we present an end-to-end table extraction and understanding system which takes a PDF file and automatically generates a set of XML and CSV files containing the extracted cells, rows and columns of tables, as well as a complete reading order analysis of the tables. Unlike many systems that work as a black-boxed, ad-hoc solution, our system design incorporates the open, reusable and extensible architecture to support research into, and development of, table-processing systems. During the demo, users will see how our system gradually transforms a PDF document into a set of structured files through a series of processing modules, namely: locating, segmenting and function/structure analysis.

Original language	English
Title of host publication	Databases Theory and Applications
Subtitle of host publication	29th Australasian Database Conference, ADC 2018, Proceedings
Editors	Junhu Wang, Gao Cong, Jinjun Chen, Jianzhong Qi
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	345-349
Number of pages	5
ISBN (Electronic)	9783319920139
ISBN (Print)	9783319920122
DOIs	https://doi.org/10.1007/978-3-319-92013-9_30
Publication status	Published - 1 Jan 2018
Event	29th Australasian Database Conference, ADC 2018 - Gold Coast, Australia Duration: 24 May 2018 → 27 May 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10837 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	29th Australasian Database Conference, ADC 2018
Country	Australia
City	Gold Coast
Period	24/05/18 → 27/05/18

Keywords

Document processing
Information extraction
Table extraction
Table processing
TEXUS

Access to Document

10.1007/978-3-319-92013-9_30

Link to publication in Scopus

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Cite this

Rastan, R., Paik, H. Y., Shepherd, J., Ryu, S. H., & Beheshti, A. (2018). TEXUS: table extraction system for PDF documents. In J. Wang, G. Cong, J. Chen, & J. Qi (Eds.), Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Proceedings (pp. 345-349). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10837 LNCS). Cham: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-92013-9_30

Rastan, Roya ; Paik, Hye Young ; Shepherd, John ; Ryu, Seung Hwan ; Beheshti, Amin. / TEXUS : table extraction system for PDF documents. Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Proceedings. editor / Junhu Wang ; Gao Cong ; Jinjun Chen ; Jianzhong Qi. Cham : Springer, Springer Nature, 2018. pp. 345-349 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "TEXUS: table extraction system for PDF documents",

abstract = "Tables in documents are a rich and under-exploited source of structured data in otherwise unstructured documents. The extraction and understanding of tabular data is a challenging task which has attracted the attention of researchers from a range of disciplines such as information retrieval, machine learning and natural language processing. In this demonstration, we present an end-to-end table extraction and understanding system which takes a PDF file and automatically generates a set of XML and CSV files containing the extracted cells, rows and columns of tables, as well as a complete reading order analysis of the tables. Unlike many systems that work as a black-boxed, ad-hoc solution, our system design incorporates the open, reusable and extensible architecture to support research into, and development of, table-processing systems. During the demo, users will see how our system gradually transforms a PDF document into a set of structured files through a series of processing modules, namely: locating, segmenting and function/structure analysis.",

keywords = "Document processing, Information extraction, Table extraction, Table processing, TEXUS",

author = "Roya Rastan and Paik, {Hye Young} and John Shepherd and Ryu, {Seung Hwan} and Amin Beheshti",

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Rastan, R, Paik, HY, Shepherd, J, Ryu, SH & Beheshti, A 2018, TEXUS: table extraction system for PDF documents. in J Wang, G Cong, J Chen & J Qi (eds), Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10837 LNCS, Springer, Springer Nature, Cham, pp. 345-349, 29th Australasian Database Conference, ADC 2018, Gold Coast, Australia, 24/05/18. https://doi.org/10.1007/978-3-319-92013-9_30

TEXUS : table extraction system for PDF documents. / Rastan, Roya; Paik, Hye Young; Shepherd, John; Ryu, Seung Hwan; Beheshti, Amin.

Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Proceedings. ed. / Junhu Wang; Gao Cong; Jinjun Chen; Jianzhong Qi. Cham : Springer, Springer Nature, 2018. p. 345-349 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10837 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

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T2 - table extraction system for PDF documents

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AU - Paik, Hye Young

AU - Shepherd, John

AU - Ryu, Seung Hwan

AU - Beheshti, Amin

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Tables in documents are a rich and under-exploited source of structured data in otherwise unstructured documents. The extraction and understanding of tabular data is a challenging task which has attracted the attention of researchers from a range of disciplines such as information retrieval, machine learning and natural language processing. In this demonstration, we present an end-to-end table extraction and understanding system which takes a PDF file and automatically generates a set of XML and CSV files containing the extracted cells, rows and columns of tables, as well as a complete reading order analysis of the tables. Unlike many systems that work as a black-boxed, ad-hoc solution, our system design incorporates the open, reusable and extensible architecture to support research into, and development of, table-processing systems. During the demo, users will see how our system gradually transforms a PDF document into a set of structured files through a series of processing modules, namely: locating, segmenting and function/structure analysis.

AB - Tables in documents are a rich and under-exploited source of structured data in otherwise unstructured documents. The extraction and understanding of tabular data is a challenging task which has attracted the attention of researchers from a range of disciplines such as information retrieval, machine learning and natural language processing. In this demonstration, we present an end-to-end table extraction and understanding system which takes a PDF file and automatically generates a set of XML and CSV files containing the extracted cells, rows and columns of tables, as well as a complete reading order analysis of the tables. Unlike many systems that work as a black-boxed, ad-hoc solution, our system design incorporates the open, reusable and extensible architecture to support research into, and development of, table-processing systems. During the demo, users will see how our system gradually transforms a PDF document into a set of structured files through a series of processing modules, namely: locating, segmenting and function/structure analysis.

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KW - Table extraction

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M3 - Conference proceeding contribution

SN - 9783319920122

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 345

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BT - Databases Theory and Applications

A2 - Wang, Junhu

A2 - Cong, Gao

A2 - Chen, Jinjun

A2 - Qi, Jianzhong

PB - Springer, Springer Nature

CY - Cham

ER -

Rastan R, Paik HY, Shepherd J, Ryu SH, Beheshti A. TEXUS: table extraction system for PDF documents. In Wang J, Cong G, Chen J, Qi J, editors, Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Proceedings. Cham: Springer, Springer Nature. 2018. p. 345-349. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-92013-9_30