Skip to main content
SpringerLink
Log in
Book cover

International Conference on Applications and Techniques in Cyber Security and Intelligence

ATCI 2017: International Conference on Applications and Techniques in Cyber Security and Intelligence pp 351–360Cite as

Research on Web Table Positioning Technology Based on Table Structure and Heuristic Rules

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 580))

Abstract

As a compact and efficient way to present relational data information, Web tables are used frequently in Web documents. Web table positioning technology are considered as essential components of Web table information extraction, and more and more people pay attention to them. This paper realizes table positioning according to Web table structure label and heuristic rules of user-definition, which includes the solution of <TABLE> nested problem, the determination of table data’s integrity, and traversal of <TABLE> tree. The experimental results show that our web table positioning method has good performance.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Hammer, J., Garcia-Molina, H., Cho, J., Aranha, R., Crespo, A.: Extracting semistructured information from the web. SIGOD Record 26(2), 18–25 (1997)

    Google Scholar 

  2. Lim, S., Ng, Y.: An automated approach for retrieving heirarchical data from HTML tables. In: the 8th International Conference on Information and Knowledge Management CIKM 1999, pp. 466–474 (1999)

    Google Scholar 

  3. Kuhlins, S., Tredwell, R.: Tookits for generating wrappers a survey of software toolkits for automated data extraction from web sites. In: International Conference NetObjectDay, pp. 184–198. Springer, Berlin (2003)

    Google Scholar 

  4. Dalvi, B., Cohen, W., Callan, J.: WebSets: extracting sets of entities from the web using unsupervised information extraction. In: the 15th International Conference on Web Search and Web Data Mining, pp. 243–252. ACM, New York (2012)

    Google Scholar 

  5. Sarma, A., Fang, L., Gupta, N., et al.: Finding related tables. In: 2012 ACM SIGMOD International Conference on Management of Data, pp. 817–828. ACM, New York (2012)

    Google Scholar 

  6. Ying, L.: Table Information Extraction Based on Web Structure. Hefei University of Technology, Hefei (2012)

    Google Scholar 

  7. Hurst, M.: Classifying table elements in HTML.: In: 11th International World Wide Web Conference, Sheraton Waikiki Honolulu, Hawaii, USA (2002). http://www2002.org/CDROM/poster/115/index.html

  8. Wang, Y., Hu, J.: A machine learning based approach for table detection on the web. In: 11th International Conference on WWW, pp. 242–250 (2002)

    Google Scholar 

  9. Tao, C.: Schema Matching and Data Extraction over HTML Tables. Brigham Young University (2003)

    Google Scholar 

  10. Chen, H., et al.: Mining tables from large scale HTML texts. In: The 18th International Conference on Computational Linguistics, pp. 166–172, ACM (2000)

    Google Scholar 

  11. Lin, K.: The Research and Implementation of Table Structure Recognition in Webpages. University of Electronic Science and technology, Chengdu (2006)

    Google Scholar 

  12. Lin, L.: Research and Implementation of Web Table Content Extraction Based on Ontology. University of Electronic Science and technology, Chengdu (2006)

    Google Scholar 

  13. Cha, S., Ma, Z., Jiao, X.: Automatic acquisition method of ontology instances from web tables. J. Northeast Univ (Natural Science) 33(3), 332–335 (2012)

    Google Scholar 

  14. Li, W., Xie, Z.: A study of visually parallel relationships in web tables based on graph models. J. Chin. Comput. Syst. 35(7), 1567–1572 (2014)

    Google Scholar 

  15. Chen, H.-H., Tsai, S.-C., Tsai, J.-H..: Mining tables from large scale html texts. In: 18th International Conference on Computational Linguistics, pp. 166–172. ACM (2000)

    Google Scholar 

  16. Penn, G., Hu, J., Luo, H., et al.: Flexible Web document analysis for delivery to narrow-band width devices. In: 5th International Conference on Document Analysis and Recognition(ICDAR), Seattle, USA, pp. 1074–1078 (2001)

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the editors and anonymous reviewers for their valuable comments. This paper is supported by the Natural Science Foundation of China (No. 61273328), the Anhui Province College Natural Science Foundation (No. KJ2016A202), and the Anhui Province College Excellent Young Talents Support Program (gxyq2017007).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China

    Tao Liao, Tianqi Liu & Shunxiang Zhang

  2. School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, China

    Zongtian Liu

Authors
  1. Tao Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tianqi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shunxiang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zongtian Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tao Liao .

Editor information

Editors and Affiliations

  1. Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, Victoria, Australia

    Jemal Abawajy

  2. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, Texas, USA

    Kim-Kwang Raymond Choo

  3. School of Computing and Mathematics, Charles Sturt University, Albury, New South Wales, Australia

    Rafiqul Islam

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Liao, T., Liu, T., Zhang, S., Liu, Z. (2018). Research on Web Table Positioning Technology Based on Table Structure and Heuristic Rules. In: Abawajy, J., Choo, KK., Islam, R. (eds) International Conference on Applications and Techniques in Cyber Security and Intelligence. ATCI 2017. Advances in Intelligent Systems and Computing, vol 580. Edizioni della Normale, Cham. https://doi.org/10.1007/978-3-319-67071-3_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67071-3_41

  • Published:

  • Publisher Name: Edizioni della Normale, Cham

  • Print ISBN: 978-3-319-67070-6

  • Online ISBN: 978-3-319-67071-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation