We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
This paper describes a system to support humanities scholars in their interpretation of literary work. It presents a user interface and web architecture that integrates text minin...
Catherine Plaisant, James Rose, Bei Yu, Loretta Au...