Abstract
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.
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References
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)
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)
Romary, L., Bonhomme, P.: Parallel alignment of structured documents. In: Véronis, J. (ed.) Parallel Text Processing, pp. 233–253. Kluwer Academic Publishers (2000)
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)
Zhang, H., Chow, T.W.S.: A coarse-to-fine framework to efficiently thwart plagiarism. Pattern Recognition 44(2), 471–487 (2011)
Wan, X.: A novel document similarity measure based on earth mover’s distance. Information Sciences 177(18), 3718–3730 (2007)
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)
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)
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)
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)
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)
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady 10(8), 707–710 (1966)
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)
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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. https://doi.org/10.1007/978-3-319-11116-2_18
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DOI: https://doi.org/10.1007/978-3-319-11116-2_18
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