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In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
Abstract. Relevance feedback (RF) has been an effective query modification approach to improving the performance of information retrieval (IR) by interactively asking a user whet...
The size of a document archive is a very important parameter for resource selection in distributed information retrieval systems. In this paper, we present a method for automatical...
Abstract In the Web search process people often think that the hardest work is done by the search engines or by the directories which are entrusted with finding the Web pages. Whi...
In this paper, we present an automated text classification system for the classification of biomedical papers. This classification is based on whether there is experimental eviden...
Min Shi, David S. Edwin, Rakesh Menon, Lixiang She...
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
Abstract. We focus on two recently proposed algorithms in the family of “boosting”-based learners for automated text classification, AdaBoost.MH and AdaBoost.MHKR . While the ...
Pio Nardiello, Fabrizio Sebastiani, Alessandro Spe...
We present in this paper a relational approach for indexing and retrieving photographs from a collection. Instead of using simple keywords as an indexing language, we propose to u...
Jean Martinet, Iadh Ounis, Yves Chiaramella, Phili...
Topic Detection and Tracking is an event-based information organization task where online news streams are monitored in order to spot new unreported events and link documents with ...
Juha Makkonen, Helena Ahonen-Myka, Marko Salmenkiv...