Abstract
Many information access applications have to tackle natural language texts that contain a large proportion of repeated and mostly invariable patterns – called boilerplates –, such as automatic templates, headers, signatures and table formats. These domain-specific standard formulations are usually much longer than traditional collocations or standard noun phrases and typically cover one or more sentences. Such motifs clearly have a non-compositional meaning and an ideal document representation should reflect this phenomenon.
We propose here a method that detects automatically and in an unsupervised way such motifs; and enriches the document representation by including specific features for these motifs. We experimentally show that this document recoding strategy leads to improved classification on different collections.
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References
Baroni, M., Chantree, F., Kilgarriff, A., Sharoff, S.: CleanEval: a competition for cleaning webpages. In: LREC (2008)
Bernstein, Y., Zobel, J.: Accurate discovery of co-derivative documents via duplicate text detection. Inf. Syst. 31(7), 595–609 (2006)
Iliopoulos, C.S., McHugh, J., Peterlongo, P., Pisanti, N., Rytter, W., Sagot, M.: A first approach to finding common motifs with gaps. International Journal of Foundation of Computer Science 16(6), 1145–1155 (2005)
Gallé, M.: Searching for Compact Hierarchical Structures in DNA by means of the Smallest Grammar Problem. Université de Rennes 1 (February 2011)
Gallé, M.: The bag-of-repeats representation of documents. In: SIGIR (2013)
Gusfield, D.: Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press (January 1997)
Kohlschütter, C., Fankhauser, P., Nejdl, W.: Boilerplate detection using shallow text features. In: WSDM, p. 441. ACM Press, New York (2010)
Kohlschütter, C., Nejdl, W.: A Densitometric Approach to Web Page Segmentation Segmentation as a Visual Problem. In: CIKM, pp. 1173–1182 (2008)
Manning, C., Raghavan, P., Schütze, H.: Introduction to Inf Retrieval. Cambridge UP (2009)
Marsan, L., Sagot, M.-F.: Extracting structured motifs using a suffix tree–algorithms and application to promoter consensus identification. Journal of Computational Biology 7(3/4), 345–362 (2000)
Pasternack, J., Roth, D.: Extracting Article Text from the Web with Maximum Subsequence Segmentation. In: WWW, pp. 971–980 (2009)
Pisanti, N., Carvalho, A.M., Marsan, L., Sagot, M.-F.: RISOTTO: Fast extraction of motifs with mismatches. In: Correa, J.R., Hevia, A., Kiwi, M. (eds.) LATIN 2006. LNCS, vol. 3887, pp. 757–768. Springer, Heidelberg (2006)
Zhang, Y., Zaki, M.: Exmotif: efficient structured motif extraction. Algorithms for Molecular Biology 1(1), 21 (2006)
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Gallé, M., Renders, JM. (2014). Boilerplate Detection and Recoding. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_42
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DOI: https://doi.org/10.1007/978-3-319-06028-6_42
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06027-9
Online ISBN: 978-3-319-06028-6
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