Web Site Audience Segmentation Using Hybrid Alignment Techniques

  • Vinh-Trung Luu
  • Germain Forestier
  • Frédéric Fondement
  • Pierre-Alain Muller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9441)


We are working on behavioral marketing in the Internet. On one hand we observe the behavior of visitors, and on the other hand we trigger (in real-time) stimulations intended to alter this behavior. Real-time and mass-customization are the two challenges that we have to address. In this paper, we present a hybrid approach for clustering visitor sessions, based on a combination of global and local sequence alignments, such as Needleman-Wunsch and Smith-Waterman. Our goal is to define very simple approaches able to address about 80 % of visitor sessions to be segmented, and which can be easily turned into small pieces of program, to be run in parallel in thousands of web browsers.


Web mining Sequential pattern mining Clustering 


  1. 1.
    Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48(3), 443–453 (1970)CrossRefGoogle Scholar
  2. 2.
    Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. J. Mol. Biol. 147(1), 195–197 (1981)CrossRefGoogle Scholar
  3. 3.
    Wang, W., Zaïane, O.R.: Clustering web sessions by sequence alignment. In: Proceedings of 13th International Workshop on Database and Expert Systems Applications, 2002, pp. 394–398. IEEE (2002)Google Scholar
  4. 4.
    Li, C., Lu, Y.: Similarity measurement of web sessions based on sequence alignment. Wuhan Univ. J. Nat. Sci. 12(5), 814–818 (2007)CrossRefGoogle Scholar
  5. 5.
    Poornalatha, G., Raghavendra, P.: Alignment based similarity distance measure for better web sessions clustering. Procedia Comput. Sci. 5, 450–457 (2011)CrossRefGoogle Scholar
  6. 6.
    Chordia, B.S., Adhiya, K.P.: Grouping web access sequences using sequence alignment method. Indian J. Comput. Sci. Eng. (IJCSE) 2(3), 308–314 (2011)Google Scholar
  7. 7.
    Dimopoulos, C., Makris, C., Panagis, Y., Theodoridis, E., Tsakalidis, A.: A web page usage prediction scheme using sequence indexing and clustering techniques. Data Knowl. Eng. 69(4), 371–382 (2010)CrossRefGoogle Scholar
  8. 8.
    Petitjean, F., Forestier, G., Webb, G., Nicholson, A., Chen, Y., Keogh, E.: Dynamic time warping averaging of time series allows faster and more accurate classification. In: IEEE International Conference on Data Mining (2014)Google Scholar
  9. 9.
    Meesrikamolkul, W., Niennattrakul, V., Ratanamahatana, C.A.: Shape-based clustering for time series data. In: Tan, P.-N., Chawla, S., Ho, C.K., Bailey, J. (eds.) PAKDD 2012, Part I. LNCS, vol. 7301, pp. 530–541. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  10. 10.
    Nakamura, A., Kudo, M.: Packing alignment: alignment for sequences of various length events. In: Huang, J.Z., Cao, L., Srivastava, J. (eds.) PAKDD 2011, Part II. LNCS, vol. 6635, pp. 234–245. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  11. 11.
    Marascu, A., Khan, S.A., Palpanas, T.: Scalable similarity matching in streaming time series. In: Tan, P.-N., Chawla, S., Ho, C.K., Bailey, J. (eds.) PAKDD 2012, Part II. LNCS, vol. 7302, pp. 218–230. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  12. 12.
    Chan, A.: An analysis of pairwise sequence alignment algorithm complexities: needleman-wunsch, smith-waterman, fasta, blast and gapped blast (2013)Google Scholar
  13. 13.
    Cooley, R., Mobasher, B., Srivastava, J.: Grouping web page references into transactions for mining world wide web browsing patterns. In: Proceedings of Knowledge and Data Engineering Exchange Workshop, 1997, pp. 2–9. IEEE (1997)Google Scholar
  14. 14.
    Cooley, R., Mobasher, B., Srivastava, J.: Data preparation for mining world wide web browsing patterns. Knowl. Inf. Syst. 1(1), 5–32 (1999)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Vinh-Trung Luu
    • 1
  • Germain Forestier
    • 1
  • Frédéric Fondement
    • 1
  • Pierre-Alain Muller
    • 1
  1. 1.MIPSUniversité de Haute AlsaceMulhouse CedexFrance

Personalised recommendations