This paper addresses the problem of extending an adaptive information filtering system to make decisions about the novelty and redundancy of relevant documents. It argues that rel...
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
The aim of our research is to produce and assess short summaries to aid users' relevance judgements, for example for a search engine result page. In this paper we present our ...
In the paper, we propose a general method for statistical performance evaluation. The method incorporates various statistical metrics and automatically selects an appropriate stat...