Fetching the paper…

Reading the bibliography…

2015

Detecting Table Region in PDF Documents Using Distant Supervision

Fan, Miao, Kim, Doo Soon

Original
PDF
Post on X

Understand

Superior to state-of-the-art approaches which compete in table recognition with 67 annotated government reports in PDF format released by {\it ICDAR 2013 Table Competition}, this paper contributes a novel paradigm leveraging large-scale unlabeled PDF documents to open-domain table detection.

We integrate the paradigm into our latest developed system ({\it PdfExtra}) to detect the region of tables by means of 9,466 academic articles from the entire repository of {\it ACL Anthology}, where almost all papers are archived by PDF format without annotation for tables.
The paradigm first designs heuristics to automatically construct weakly labeled data.
It then feeds diverse evidences, such as layouts of documents and linguistic features, which are extracted by {\it Apache PDFBox} and processed by {\it Stanford NLP} toolkit, into different canonical classifiers.

Detecting Table Region in PDF Documents Using Distant Supervision · Around

Built on

B. Yildiz, K. Kaiser, and S. Miksch, “pdf2table: A method to extract table information from pdf files,” in IICAI , 2005, pp. 1773–1785
2005
Earlier work this paper cites.
Y. Liu, P. Mitra, and C. L. Giles, “Identifying table boundaries in digital documents via sparse line detection,” in Proceedings of the 17th ACM Conference on Information and Knowledge Management , ser. CIKM ’08. New York, NY, USA: ACM, 2008, pp. 1311–1320. [Online]. Available: http://doi.acm.org/10.1145/1458082.1458255
Original
2008
Earlier work this paper cites.
E. Oro and M. Ruffolo, “Pdf-trex: An approach for recognizing and extracting tables from pdf documents,” in Document Analysis and Recognition, 2009. ICDAR’09. 10th International Conference on . IEEE, 2009, pp. 906–910
2009
Earlier work this paper cites.

Similar

M. Gobel, T. Hassan, E. Oro, and G. Orsi, “Icdar 2013 table competition,” in Document Analysis and Recognition (ICDAR), 2013 12th International Conference on . IEEE, 2013, pp. 1449–1453
2013
Cited alongside, same era.
S. Klampfl, K. Jack, and R. Kern, “A comparison of two unsupervised table recognition methods from digital scientific articles,” D-Lib Magazine , vol. 20, no. 11, p. 7, 2014
2014
Cited alongside, same era.

Then

M. Fan, D. Zhao, Q. Zhou, Z. Liu, T. F. Zheng, and E. Y. Chang, “Distant supervision for relation extraction with matrix completion,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics , vol. 1, 2014, pp. 839–849
2014
Later among the works it cites.
M. Fan, Q. Zhou, and T. F. Zheng, “Distant supervision for entity linking,” arXiv preprint arXiv:1505.03823 , 2015
Original
2015
Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…