—In this paper, we propose a probabilistic algorithm for detecting near duplicate text, audio, and video resources efficiently and effectively in large-scale P2P systems. To thi...
Odysseas Papapetrou, Sukriti Ramesh, Stefan Siersd...
In this paper, we present a novel near-duplicate document detection method that can easily be tuned for a particular domain. Our method represents each document as a real-valued s...
Hannaneh Hajishirzi, Wen-tau Yih, Aleksander Kolcz
Detection of near duplicate documents is an important problem in many data mining and information filtering applications. When faced with massive quantities of data, traditional d...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
We propose a multiple source domain adaptation method, referred to as Domain Adaptation Machine (DAM), to learn a robust decision function (referred to as target classifier) for l...
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...