Our idea of concept pair clustering is a two-step clustering process: first it clusters concept pairs into clusters with good precision using dependency patterns; then it improves the coverage of the clusters using surface patterns.
the standard k-means algorithm is affected by the choice of seeds and the number of clusters k. as we claimed in the Introduction section, because we aim to extract relations from Wikipedia articles in an unsupervised manner, cluster number k is unknown and no good centroids can be predicted.