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Indexing and querying segmented web pages: the BlockWeb Model

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Abstract

We present in this paper a model for indexing and querying web pages, based on the hierarchical decomposition of pages into blocks. Splitting up a page into blocks has several advantages in terms of page design, indexing and querying such as (i) blocks of a page most similar to a query may be returned instead of the page as a whole (ii) the importance of a block can be taken into account, as well as (iii) the permeability of the blocks to neighbor blocks: a block b is said to be permeable to a block b′ in the same page if b′ content (text, image, etc.) can be (partially) inherited by b upon indexing. An engine implementing this model is described including: the transformation of web pages into blocks hierarchies, the definition of a dedicated language to express indexing rules and the storage of indexed blocks into an XML repository. The model is assessed on a dataset of electronic news, and a dataset drawn from web pages of the ImagEval campaign where it improves by 16% the mean average precision of the baseline.

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References

  1. Bruno, E., Faessel, N., Glotin, H., Le Maitre, J., Scholl, M.: Indexing by permeability in block structured web pages. In: Proceedings of the 9th ACM Symposium on Document Engineering (DocEng 2009), pp. 70–73, (2009) (short paper)

  2. Bruno, E., Faessel, N., Le Maitre, J., Scholl, M.: Blockweb: an IR model for block structured web pages. In: Proc. of 7th Int. Workshop on Content Based Multimedia Indexing (CBMI 2009), pp. 219–224. Chania, Crete, June 3–5 (2009)

  3. Cai, D., He, X., Li, Z., Ma, W.-Y., Wen, J.-R.: Hierarchical clustering of WWW image search results using visual, textual and link information. In: Proc. of the 12th ACM Int. Conf. on Multimedia, MULTIMEDIA ’04, pp. 952–959. ACM, New York, NY, USA (2004)

    Chapter  Google Scholar 

  4. Cai, D., Yu, S., Wen, J.-R., Ma, W.-Y.: VIPS: A Vision-Based Page Segmentation Algorithm. Technical report, Microsoft Research (2003)

  5. Cui, H., Wen, J.: Hierarchical indexing and flexible element retrieval for structured documents. In: Proc. of the 25th European Conf. on IR Research (ECIR 2003), pp. 73–87. Pisa, Italy (2003)

  6. Debnath, S., Mitra, P., Pal, N., Giles, C.L.: Automatic identification of informative sections of web pages. IEEE Trans. Knowl. Data Eng. 17(9), 1233–1246 (2005)

    Article  Google Scholar 

  7. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley-Interscience (2000)

  8. Ha, J., Haralick, R.M., Phillips, I.T.: Recursive X-Y cut using bounding boxes of connected components. In: Proc. of the Third International Conference on Document Analysis and Recognition (ICDAR’95), vol. 2, pp. 952–955. Washington, DC, USA (1995)

  9. Lin, S.-H., Ho, J.-M.: Discovering informative content blocks from Web documents. In: Proc. of the 8th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pp. 588–593. Edmonton, Alberta, Canada (2002)

  10. Moëllic, P.A., Fluhr, C.: ImagEval 2006 official campaign. CEA List (2006)

  11. Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18(11), 613–620 (1975)

    Article  MATH  Google Scholar 

  12. Song, R., Liu, H., Wen, J.-R., Ma, W.-Y.: Learning block importance models for web pages. In: Proc. of the 13th Int. Conf. on World Wide Web (WWW 2004), pp. 203–211. Manhattan, NY, USA (2004)

  13. Tollari, S., Glotin, H.: Web image retrieval on ImagEVAL: Evidences on visualness and textualness concept dependency in fusion model. In: Proc. of the ACM Int. Conf. on Image and Video Retrieval (CIVR 2007), pp. 65–72 (2007)

  14. Tollari, S., Glotin, H.: Learning optimal visual features from web sampling in online image retrieval. In: IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 2008, pp. 1229–1232. IEEE (2008)

  15. Vadrevu, S., Gelgi, F., Davulcu, H.: Information extraction from web pages using presentation regularities and domain knowledge. World Wide Web 10(2), 157–179 (2007)

    Article  Google Scholar 

  16. Yi, L., Liu, B., Li, X.: Eliminating noisy information in web pages for data mining. In: Proc of the 9th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pp. 296–305. Washington, DC, USA, ACM (2003)

  17. Zou, J., Le, D., Thoma, G.R.: Combining DOM tree and geometric layout analysis for online medical journal article segmentation. In: Proc. of the 6th ACM/IEEE-CS Joint Conf. on Digital Libraries, pp. 119–128. Chapel Hill, North Carolina, USA (2006)

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Correspondence to Emmanuel Bruno.

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Bruno, E., Faessel, N., Glotin, H. et al. Indexing and querying segmented web pages: the BlockWeb Model. World Wide Web 14, 623–649 (2011). https://doi.org/10.1007/s11280-011-0124-6

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  • DOI: https://doi.org/10.1007/s11280-011-0124-6

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Mathematics Subject Classifications (2010)

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