In this paper we propose a completely unsupervised method for open-domain entity extraction and clustering over query logs. The underlying hypothesis is that classes defined by mi...
Previous research in cross-document entity coreference has generally been restricted to the offline scenario where the set of documents is provided in advance. As a consequence, t...
We present and analyze the star clustering algorithm. We discuss an implementation of this algorithm that supports browsing and document retrieval through information organization...
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Approximation structuring clustering is an extension of what is usually called square-error clustering" onto various cluster structures and data formats. It appears to be not...