Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion met...
In this paper, we propose a machine learning algorithm for shallow semantic parsing, extending the work of Gildea and Jurafsky (2002), Surdeanu et al. (2003) and others. Our algor...
Sameer Pradhan, Wayne Ward, Kadri Hacioglu, James ...
We discuss the problem of clustering elements according to the sources that have generated them. For elements that are characterized by independent binary attributes, a closedform...
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Correlation is one of the most widely used similarity measures in machine learning like Euclidean and Mahalanobis distances. However, compared with proposed numerous discriminant ...