Abstract
Web mining is the application of data mining techniques to gather useful information from the World Wide Web. The rapid increase in digital use makes web usage mining (a subtype of web mining) important. To tackle the issues in web usage mining, we introduce a combination of hierarchical user emotion analysis and a self-organizing mapping algorithm in the training and testing of a recommended system. This method identifies the least dissimilar element, which will not last, and prefers the highest priority element in the cluster. The quality of the proposed system is evaluated in terms of entropy, purity, and Davies-Bouldin index. The proposed method is compared with various traditional clustering approaches such as ant colony clustering, k-means clustering, and genetic algorithm. The experimental results show that our proposed system provides 40% better quality when compared with traditional clustering approaches.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Etzioni, The world wide web: quagmire or gold mine? Comm. ACM 39, 65–98 (1996)
P. Kolari, A. Joshi, Web mining: research and practice. Comput. Sci. Eng. 6(4), 49–53 (2004)
D. Tanasa, B. Trousse, Advanced data preprocessing for intersites web usage mining. IEEE Intell. Syst. 19(2), 59–65 (2004)
O. Nasraoui, M. Soliman, E. Saka, A. Badia, R. Germain, A web usage mining framework for mining evolving user profiles in dynamic web sites. IEEE Trans. Knowl. Data Eng. 20(2), 202–215 (2008)
S.G. Petridou, V.A. Koutsonikola, A.I. Vakali, G.I. Papadimitriou, Time aware web users clustering. IEEE Trans. Knowl. Data Eng. 20(5), 653–667 (2007)
A. Kundu, E. Bertino, A new model for secure dissemination of XML content. IEEE Trans. Syst. Man. Cybern. Part C Appl. Rev. 38(3), 292–301 (2008)
M.K. Agarwal, G. Kar, R. Mahindru, A. Neogi, A. Saile, Performance problem prediction in transaction-based e-business systems. IEEE Trans. Netw. Serv. Manag. 5(1), 1–10 (2008)
D. Pierrakos, G. Paliouras, Personalizing web directories with the aid of web usage data. IEEE Trans. Knowl. Data Eng. 22(9), 1331–1344 (2010)
M.H. Chehreghani, C. Lucas, M. Rahgozar, OInduced: an efficient algorithm for mining induced patterns from rooted ordered trees. IEEE Trans. Syst. Man. Cybern. Part A Syst. Hum. 41(5), 1013–1036 (2011)
C.C. Chen, Z.Y. Chen, C.Y. Wu, An unsupervised approach for person name bipolarization using principal component analysis. IEEE Trans. Knowl. Data Eng. 24(11), 170–178 (2012)
A. Abraham, V. Ramos, Web usage mining using artificial ant colony clustering and linear genetic programming. Congr. Evol. Comput. 2, 1384–1391 (2003)
M.M.V. Hulle, Self organising maps, in Handbook of Natural Computing, (Springer, Berlin, 2012), pp. 585–622
P.N. Tan, M. Stenbach, V. Kumar, Introduction to Data Mining (Addison Wesley, Boston, 2005), pp. 1–6
D.L. Davies, D.W. Bouldin, Cluster separation measure. IEEE Trans. Pattern Anal. Mach. Intell. 1, 95–104 (1979)
M. Alphy, A. Sharma, Study on online community user motif using web usage mining. J. Phys. Conf. Ser. 710, 012015 (2016)
The Jester Dataset. https://grouplens.org/datasets/jester/. 07 / 07/ 2001
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Alphy, M., Sharma, A. (2018). An Improved Hybrid Algorithm for Web Usage Mining. In: Woungang, I., Dhurandher, S. (eds) International Conference on Wireless, Intelligent, and Distributed Environment for Communication. WIDECOM 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-75626-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-75626-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-75625-7
Online ISBN: 978-3-319-75626-4
eBook Packages: EngineeringEngineering (R0)