Hierarchical Matching of Traffic Information Services Using Semantic Similarity

Algorithm 1

TIS clustering based on K-means.

Input:

Service: set of service profiles

Output:

k: number of centers of clusters

Begin

textVect ←processData(Service)

 cluster_Num ← k, error← INF

 randowWithServiceCategory(textVect)

 while errori < errori−1  do

Kmeans(textVect, cluster_Num)

errori←getError(textVect)

serviceCategory ←getServiceCategory(textVect)

cluster ←getServiceCluster(serviceCategory, textVect)

 end while

End