Abstract
We present WBPL (Web users Behavior Prediction Library), a cross-platform open-source library for predicting the behavior of web users. WBPL allows training prediction models from server logs. The proposed library offers support for three of the most used webservers (Apache, Nginx and Lighttpd). Models can then be used to predict the next resources fetched by users and can be updated with new logs efficiently. WBPL offers multiple state-of-the-art prediction models such as PPM, All-K-Order-Markov and DG and a novel prediction model CPT (Compact Prediction Tree). Experiments on various web click-stream datasets shows that the library can be used to predict web surfing or buying behaviors with a very high overall accuracy (up to 38 %) and is very efficient (up to 1000 predictions /s).
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References
Cleary, J., Witten, I.: Data compression using adaptive coding and partial string matching. IEEE Trans. on Inform. Theory 24(4), 413–421 (1984)
Deshpande, M., Karypis, G.: Selective Markov models for predicting Web page accesses. ACM Transactions on Internet Technology 4(2), 163–184 (2004)
Google Prediction API, https://developers.google.com/prediction (accessed: February 15, 2014)
Gueniche, T., Fournier-Viger, P., Tseng, V.-S.: Compact Prediction Tree: A Lossless Model for Accurate Sequence Prediction. In: Motoda, H., Wu, Z., Cao, L., Zaiane, O., Yao, M., Wang, W. (eds.) ADMA 2013, Part II. LNCS (LNAI), vol. 8347, pp. 177–188. Springer, Heidelberg (2013)
Hassan, M.T., Junejo, K.N., Karim, A.: Learning and Predicting Key Web Navigation Patterns Using Bayesian Models. In: Gervasi, O., Taniar, D., Murgante, B., Laganà, A., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2009, Part II. LNCS, vol. 5593, pp. 877–887. Springer, Heidelberg (2009)
HMMgene (v. 1.1), http://www.cbs.dtu.dk/services/HMMgene (accessed: February 15, 2014)
Padmanabhan, V.N., Mogul, J.C.: Using Prefetching to Improve World Wide Web Latency. Computer Communications 16, 358–368 (1998)
Domenech, J., de la Ossa, B., Sahuquillo, J., Gil, J.A., Pont, A.: A taxonomy of web prediction algorithms. Expert Systems with Applications (9) (2012)
Pitkow, J., Pirolli, P.: Mining longest repeating subsequence to predict world wide web surng. In: Proc. 2nd USENIX Symposium on Internet Technologies and Systems, Boulder, CO, pp. 13–25 (1999)
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Gueniche, T., Fournier-Viger, P., Nkambou, R., Tseng, V.S. (2014). WBPL: An Open-Source Library for Predicting Web Surfing Behaviors. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_55
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DOI: https://doi.org/10.1007/978-3-319-08326-1_55
Publisher Name: Springer, Cham
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