Abstract
Mobile phones are the most significant way of communication in this era and SMS is the extensively used mobile service around the globe. This extensive use of SMS puts oil into fire of competition between different telecom companies. Only the one who manages to make subscribers believe “We care for you” can survive, obviously keeping company’s own benefits and profits in mind. This research paper presents a technique to effectively design and develop smart SMS packages by using contextual information of SMS data. It also deals with the prediction of multiple patterns about subscriber’s behaviour by using subscribers demographic and timing information.
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
Preview
Unable to display preview. Download preview PDF.
References
Zerfos, P., Meng, X., Wong, S.H.Y., Samanta, V., Lu, S.: A study of short message service of a nationwide cellular network. In: Proc. of ACM SIGCOMM Internet Measurement Conference (IMC), Rio de Janeiro (2006)
Sarawagi, S.: Information Extraction. Foundations and Trends in Databases 1(3) (2008)
White, R.W., Bailey, P., Chen, L.: Predicting User Interests from Contextual Information. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (2009)
Heath, T., Motta, E., Dzbor, M.: Uses of Contextual Information to Support Online Tasks. In: 1st AKT Doctoral Symposium, Milton Keynes, UK, June 14-16 (2005)
Cooper, R., Ali, S.: Extracting Data from Personal Text Messages (2006)
Aumann, Y., Feldman, R., Liberzon, Y., Rosenfeld, B., Schler, J.: Visual Information Extraction. Knowledge and Information Systems (2006)
Chang, C.-H., Kayed, M., Girgis, M.R., Shaalan, K.: Survey of Web Information Extraction Systems. IEEE Transactions on Knowledge and Data Engineering, TKDE-0475-1104.R3 (2006)
Tamames, J., de Lorenzo, V.: EnvMine: A text mining systemfor the automatic extraction of contextual information (2010)
Chen, J., Linn, B., Subramanian, L.N.: SMS-Based Contextual Web Search. In: Proceedings of the 1st ACM Workshop on Networking, Systems, and Applications for Mobile Handhelds (2009)
Ramayah, T., Yulihasri, E., Ibrahim, A., Jamaludin, N.: Predicting Short Message Service (SMS) Usage among University Students using the Technology Acceptance Model (TAM). In: 15th International Conference on Management of Technology (IAMOT 2006), Beijing, P.R. China, May 22-26 (2006)
Phau, I., Teah, M.: Young consumers’ motives for using SMS and perceptions towards SMS advertising. Direct Marketing: An International Journal 3(2), 97–108 (2009)
Karim, N.S.A., Oyefolahan, I.O.: Mobile Phone Appropriation: Exploring Differences in terms of Age, Gender and Occupation. In: The 6th International Conference on Information Technology and Applications, ICITA 2009 (2009)
Balkrishman, V., Yellow, P.H.P.: Texting satisfaction: does age and gender make a difference. International Journal of Computer Science and Security (2007)
Ahmed, I., Nawaz, M.M., Ahmad, Z., Shaukat, M.Z., Usman, A., Ahmed, S.: Impact of Demographical Factors and Extent of SMS usage on Customer Satisfaction and Retention. Interdiscilinary Journal of Contemporary Research in Business (2010)
Hanif, M., Hafeez, S., Riaz, A.: Factors Affecting Customer Satisfaction. International Research Journal of Finance & Economics (60), 44 (2010)
Amailef, K., Lu, J., Ma, J.: Text Information Extraction and aggregation in a mobile based emergency response system (2009)
Chen, D.-Y., Wang, J.-J., Chen, C.-H., Chen, Y.-S.: Video based intelligent vehicle contextual information extraction for night conditions
Insignt into Data Mining (theory and Practice) Book
Saar-Tsechansky, M., Provost, F.: Handling Missing values when applying classification models. Journal of Machine Learning Research (2007)
Allison, P.D.: Multiple imputation for missing data: A cautionary tale. Sociological Methods of Research 28(3), 301–309 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Butt, A.J., Butt, N.A., Butt, R.G., Ikram, M.T. (2014). Predicting Mobile Subscriber’s Behaviour from Contextual Information Extraction: SMS Data. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_80
Download citation
DOI: https://doi.org/10.1007/978-3-319-12643-2_80
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12642-5
Online ISBN: 978-3-319-12643-2
eBook Packages: Computer ScienceComputer Science (R0)