In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
We propose an agent for exploring and categorizing documents on the World Wide Web based on a user pro le. The heart of the agent is an automatic categorization of a set of docume...
Eui-Hong Han, Daniel Boley, Maria L. Gini, Robert ...
In this paper, we present the results of our work that seek to negotiate the gap between low-level features and high-level concepts in the domain of web document retrieval. This wo...
In this paper we study duplicates on the Web, using collections containing documents of all sites under the .cl domain that represent accurate and representative subsets of the We...
Effective representation of Web search results remains an open problem in the Information Retrieval community. For ambiguous queries, a traditional approach is to organize search ...