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Publications (4)

1Rank Distance as a Stylistic Similarity2008  Marius Popescu,Liviu P. Dinuin a way or another, there was always a need for a distance function to measure similarity (more precisely dissimilarity)...

2Learning Greek Verb Complements: Addressing the Class Imbalance(Stanfill and Waltz 1986) besides the broadly used Euclidean distance. The former is more suitable for this type of features...described in this section. The most commonly used distance function is the Euclidean distance. One drawback of the Euclidean...

3Expected Error Minimization with Ultraconservative Update for SMTri; eˆ( fi;W ) n i=1 , (3) where d(W,Wk) is a distance function of a pair of weights and it is used to penalize a weight...pseudodocument. 3.2 Distance Metric Based on Projection Euclidean distance ( L2 norm) is usually employed as in MIRA (Watanabe...

4Inverse Document Density: A Smooth Measure for LocationDependent Term Irregularitiesthis equation, d(x , y) is a distance metric, e.g. the Euclidean distance in case of samples from Rn. The function K is the kernel...document density of t at x . In these equations the distance function must be matched to the coordinate space that has been...