By Elizabeth Bradley, Nancy Collins, W. Philip Kegelmeyer (auth.), Frank Hoffmann, David J. Hand, Niall Adams, Douglas Fisher, Gabriela Guimaraes (eds.)
This e-book constitutes the refereed court cases of the 4th foreign convention on clever info research, IDA 2001, held in Cascais, Portugal, in September 2001.
The 37 revised complete papers offered have been rigorously reviewed and chosen from a complete of just about a hundred and fifty submissions. All present points of this interdisciplinary box are addressed; the parts lined comprise information, synthetic intelligence, neural networks, computing device studying, information mining, and interactive dynamic info visualization.
Read Online or Download Advances in Intelligent Data Analysis: 4th International Conference, IDA 2001 Cascais, Portugal, September 13–15, 2001 Proceedings PDF
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Extra info for Advances in Intelligent Data Analysis: 4th International Conference, IDA 2001 Cascais, Portugal, September 13–15, 2001 Proceedings
Ca Abstract. Re-Sampling methods are some of the diﬀerent types of approaches proposed to deal with the class-imbalance problem. Although such approaches are very simple, tuning them most eﬀectively is not an easy task. In particular, it is unclear whether oversampling is more effective than undersampling and which oversampling or undersampling rate should be used. This paper presents an experimental study of these questions and concludes that combining diﬀerent expressions of the resampling approach in a mixture of experts framework is an eﬀective solution to the tuning problem.
3p Avg. 4 Table 4. Main characteristics of the used collections. Term reweighting and query expansion experiments. even using qe1, with the same pattern as CACM. Finally, CISI exhibits a quite uniform behaviour across the diﬀerent weighting methods. 6 Concluding Remarks In this paper we have introduced a relevance feedback method for the Bayesian Network Retrieval model based on partial evidences. We have presented the theoretical frame over it is based on, and empirically shown how this method has a robust behaviour with four of the ﬁve standard test collections that we have used.
Acknowledgments The author would like to acknowledge B. BouchonMeunier for her help and her useful suggestions. 5 Conclusion In this paper, we present an approach based on fuzzy multidimensional databases to automatically extract fuzzy summaries from large databases. Multidimensional databases are a good means to browse through granularity levels. Moreover, they have been extended to the management of imperfect data and ﬂexible queries in our recent work. We also study the link between association rules and fuzzy summaries, especially in the case of multidimensional databases.