LE Baum, T Petrie, G Soules, and N Weiss, ‘A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains’, The Annals of MathematicaStatistics, 41(1), 164–171, (1970).
MJA Berry and GS Linoff, Data mining techniques: for marketing, sales, and customer relationship management, Wiley New York, 2004.
LA Cox Jr and DA Popken, ‘A hybrid system-identification method for forecasting telecommunications product demands’, International Journal of Forecasting, 18(4), 647–671, (2002).
M Deshpande and G Karypis, ‘Selective markov models for predicting web page accesses’, ACM Transactions on Internet Technology (TOIT), 4(2), 163–184, (2004).
M Eirinaki, M Vazirgiannis, and D Kapogiannis, ‘Web path recommendations based on page ranking and markov models’, in Proceedings of the 7th annual ACM international workshop on Web information and data management, WIDM ’05, pp. 2–9, (2005).
O Netzer, J Lattin, and VS Srinivasan, ‘A hidden markov model of customer relationship dynamics’, (2007).
A Papoulis, Probability, Random Variables and Stochastic Processes, 1991.
J Pitkow and P Pirolli, ‘Mining longest repeating subsequences to predict world wide web surfing’, in The 2nd USENIX Symposium on Internet Technologies & Systems, pp. 139–150, (1999).
D Ruta and B Majeed, ‘Business process forecasting in telecommunication industry’, 1–5, (2010).
P Taylor, M Leida, and BA Majeed, ‘Case study in process mining in a multinational enterprise’, in Lecture Notes in Business Information Processing. Springer, (2012).
S Thede and M Happer, ‘A second-order hidden markov model for part-of-speech tagging’, 175–182, (1999).
W van der Aalst, Process mining: Discovery, conformance and enhancement of business processes,Springer-Verlag, Berlin, 2011.
M Waterman, ‘Estimating statistical significance of sequence alignments’, Philosophical transactions-Royal society of London series B biological sciences, 344, 383–390, (1994).