Generalized vector spaces model in information retrieval
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Information Retrieval
Similarity Model and Term Association for Document Categorization
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
Survey of Text Mining
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Document representation using global association distance model
ECIR'07 Proceedings of the 29th European conference on IR research
Formal distance vs. association strength in text processing
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
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In this paper we present a new model, designated as Association Graph, to improve document representation, facilitating the ontological dimension. We explain how to generate and use this kind of graph. Also, we analyze different document similarity measures based on this representation. A classical vector space model was used to evaluate this model and measures, investigating their strengths and weaknesses. The proposed model was found to give promising results.