Abstract
A great amount of information is still being stored in loosely structured documents in several widely used formats. Due to the lack of data description in these documents, their integration to the existing information systems requires sophisticated pre-processing techniques to be developed. To the document reader, the content structure is mostly presented by visual means. Therefore, we propose a technique for the discovery of the logical document structure based on the analysis of various visual properties of the document such as the page layout or text properties. This technique is currently being tested and some promising preliminary results are available.
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References
Chen, J., et al.: Function-based object model towards website adaptation. In: Proceedings of the 10th International Wold Wide Web Conference (2001)
Gupta, S., et al.: Dom-based content extraction of html documents. In: WWW2003 proceedings of the 12 Web Conference, pp. 207–214 (2003)
Kovacevic, M., et al.: Recognition of common areas in a web page using visual information: a possible application in a page classification. In: Proceedings of 2002 IEEE International Conference on Data (2002)
Mukherjee, S., et al.: Automatic discovery of semantic structures in html documents. In: International Conference on Document Analysis and Recognition, IEEE Computer Society Press, Los Alamitos (2003)
Cai, D., et al.: VIPS: a Vision-based Page Segmentation Algorithm. Microsoft Research (2003)
Gu, X.D., et al.: Visual based content understanding towards web adaptation. In: Proc. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 164–173 (2002)
Hassan, T., Baumgartner, R.: Intelligent wrapping from pdf documents with lixto. In: RAWS 2005, FEI VB, pp. 17–24 (2005)
Chung, C.Y., Gertz, M., Sundaresan, N.: Reverse engineering for web data: From visual to semantic structures. In: 18th International Conference on Data Engineering, IEEE Computer Society Press, Los Alamitos (2002)
Yang, Y., Zhang, H.: HTML page analysis based on visual cues. In: ICDAR ’01: Proceedings of the Sixth International Conference on Document Analysis and Recognition, Seattle, Seattle, USA, p. 859. IEEE Computer Society, Los Alamitos (2001)
Gatterbauer, W., Bohunsky, P.: Table extraction using spatial reasoning on the CSS2 visual box model. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAIÂ 2006), July 2006, MIT Press, Cambridge (2006)
Kruepl, B., Herzog, M.: Visually guided bottom-up table detection and segmentation in web documents. In: WWW ’06: Proceedings of the 15th international conference on World Wide Web, pp. 933–934. ACM Press, New York (2006)
Burget, R.: Hierarchies in html documents: Linking text to concepts. In: 15th International Workshop on Database and Expert Systems Applications, pp. 186–190. IEEE Computer Society, Los Alamitos (2004)
Song, R., et al.: Learning block importance models for web pages. In: WWW ’04: Proceedings of the 13th international conference on World Wide Web, pp. 203–211. ACM Press, New York (2004)
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Burget, R. (2007). Automatic Document Structure Detection for Data Integration. In: Abramowicz, W. (eds) Business Information Systems. BIS 2007. Lecture Notes in Computer Science, vol 4439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72035-5_30
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DOI: https://doi.org/10.1007/978-3-540-72035-5_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72034-8
Online ISBN: 978-3-540-72035-5
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