clickstream (version 1.0)

predict-methods: Predicts the next click(s) of a user

Description

This method predicts the next click(s) of a user. The first clicks of a user are given as Pattern object. The next click(s) are predicted based on the transition probabilities in the MarkovChain object. The probability distribution of the next click (n) is estimated as follows: $$X^{(n)}=\sum_{i=1}^k \lambda_iQ_iX^{(n-i)}$$

Arguments

object

A MarkovChain object used for predicting the next click(s)

startPattern

The first clicks of a user as Pattern object. A Pattern object with an empty sequence is also possible.

dist

(Optional) The number of clicks that should be predicted (default is 1).

ties

(Optional) The strategy for handling ties in predicting the next click. Possible strategies are random (default) and first.

See Also

fitMarkovChain

Examples

# fitting a simple Markov chain and predicting the next click
clickstreams<-c("User1,h,c,c,p,c,h,c,p,p,c,p,p,o",
               "User2,i,c,i,c,c,c,d",
               "User3,h,i,c,i,c,p,c,c,p,c,c,i,d",
               "User4,c,c,p,c,d",
               "User5,h,c,c,p,p,c,p,p,p,i,p,o",
               "User6,i,h,c,c,p,p,c,p,c,d")
csf<-tempfile()
writeLines(clickstreams, csf)
cls<-readClickstreams(csf, header=TRUE)
mc<-fitMarkovChain(cls)
startPattern<-new("Pattern", sequence=c("h", "c"))
predict(mc, startPattern)