Skip to main content

A Method for Fine-Grained Document Alignment Using Structural Information

  • Conference paper
Web Technologies and Applications (APWeb 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8709))

Included in the following conference series:


It is useful to understand the corresponding relationships between each part of related documents, such as a conference paper and its modified version published as a journal paper, or documents in different versions. However, it is hard to associate corresponding parts which have been heavily modified only using similarity in their content. We propose a method of aligning documents considering not only content information but also structural information in documents. Our method consists of three steps; baseline alignment considering document order, merging, and swapping. We used papers which have been presented at a domestic conference and an international conference, then obtained their alignments by using several methods in our evaluation experiments. The results revealed the effectiveness of the use of document structures.

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

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Daumé III, H., Marcu, D.: A phrase-based HMM approach to document/abstract alignment. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, Barcelona, Spain, pp. 119–126 (July 2004)

    Google Scholar 

  2. Jeong, M., Titov, I.: Multi-document topic segmentation. In: Proceedings of the 19th ACM Conference on Information and Knowledge Management, pp. 1119–1128 (October 2010)

    Google Scholar 

  3. Romary, L., Bonhomme, P.: Parallel alignment of structured documents. In: Véronis, J. (ed.) Parallel Text Processing, pp. 233–253. Kluwer Academic Publishers (2000)

    Google Scholar 

  4. Zhang, H., Chow, T.W.S.: A multi-level matching method with hybrid similarity for document retrieval. Expert Systems with Applications 39(3), 2710–2719 (2012)

    Article  Google Scholar 

  5. Zhang, H., Chow, T.W.S.: A coarse-to-fine framework to efficiently thwart plagiarism. Pattern Recognition 44(2), 471–487 (2011)

    Article  MathSciNet  Google Scholar 

  6. Wan, X.: A novel document similarity measure based on earth mover’s distance. Information Sciences 177(18), 3718–3730 (2007)

    Article  Google Scholar 

  7. Tekli, J., Chbeir, R.: A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics. Journal of Web Semantics 11, 14–40 (2012)

    Article  Google Scholar 

  8. Yahyaei, S., Bonzanini, M., Roelleke, T.: Cross-lingual text fragment alignment using divergence from randomness. In: Grossi, R., Sebastiani, F., Silvestri, F. (eds.) SPIRE 2011. LNCS, vol. 7024, pp. 14–25. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  9. Au Yeung, C., Duh, K., Nagata, M.: Providing cross-lingual editing assistance to wikipedia editors. In: Gelbukh, A. (ed.) CICLing 2011, Part II. LNCS, vol. 6609, pp. 377–389. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  10. Smith, J.R., Quirk, C., Toutanova, K.: Extracting parallel sentences from comparable corpora using document level alignment. In: Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Los Angeles, USA, pp. 403–411 (June 2010)

    Google Scholar 

  11. Vu, T., Aw, A., Zhang, M.: Feature-based method for document alignment in comparable news corpora. In: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, Athens, Greece, pp. 843–851 (2009)

    Google Scholar 

  12. Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady 10(8), 707–710 (1966)

    MathSciNet  Google Scholar 

  13. Zhang, K., Shasha, D.: Simple fast algorithms for the editing distance between trees and related problems. SIAM Journal on Computing 18(6), 1245–1262 (1989)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Tsujio, N., Shimizu, T., Yoshikawa, M. (2014). A Method for Fine-Grained Document Alignment Using Structural Information. In: Chen, L., Jia, Y., Sellis, T., Liu, G. (eds) Web Technologies and Applications. APWeb 2014. Lecture Notes in Computer Science, vol 8709. Springer, Cham.

Download citation

  • DOI:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11115-5

  • Online ISBN: 978-3-319-11116-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics