In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
Coreferencing entities across documents in a large corpus enables advanced document understanding tasks such as question answering. This paper presents a novel cross document core...
Jian Huang 0002, Sarah M. Taylor, Jonathan L. Smit...
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
Abstract— In this paper we suggest a new approach to represent text document collections, integrating background knowledge to improve clustering effectiveness. Background knowled...
This paper aims to introduce the robustness against noise into the spectral clustering algorithm. First, we propose a warping model to map the data into a new space on the basis o...