21. The method of claim 18 , wherein each entry in the sparse vector a of the compact representation is proportional to a probability that a feature is observed given an execution environment.
18. The method of claim 17 , further comprising the steps of: selecting one or more of the zeta words to be anchor words; encoding in a vector a ζ , the probabilities of the anchor words, given that the process snippet contains one or more zeta words; creating a sparse vector a μ , that estimates the probabilities for the non-zeta words in the process snippet; and combining by direct weighted sum the vector a ζ and the sparse vector a μ into the sparse vector a of the process dot: 
 a=b ζ a ζ ⊕b μ a μ with weights b ζ and b μ .