this paper uses a set of 3D geometric measures withthe purpose of characterizing lung nodules as malignant or benign. Based on a sample of 36 nodules, 29 benign and 7 malignant, these measures are analyzed with a tec...
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Recently applying artificial intelligence, machinelearning and datamining techniques to intrusion detection system are increasing. But most of researches are focused on improving the performance of classifier. Selec...
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the real transactional databases often exhibit temporal characteristic and time varying behavior. Temporal association rule has thus become an active area of research. A calendar unit such as months and days, clock un...
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We introduce an algorithm for mining expressive temporal relationships from complex data. Our algorithm, AprioriSetsAndSequences (ASAS), extends the Apriori algorithm to data sets in which a single data instance may c...
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When we mine information for knowledge on a whole data streams it's necessary to cope with uncertainty as only a part of the stream is available. We introduce a stastistical technique, independant from the used al...
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Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have their labels. Although there is a straig...
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In the information age, data is pervasive. In some applications, data explosion is a significant phenomenon. the massive data volume poses challenges to both human users and computers. In this project, we propose a ne...
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Assessing the similarity between objects is a prerequisite for many datamining techniques. this paper introduces a novel approach to learn distance functions that maximizes the clustering of objects belonging to the ...
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In this paper there will be presented the new opportunities for applying linguistic algorithms of patternrecognition for computer understanding of image semantic content in intelligent information systems. A successf...
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In this paper there will be presented the new opportunities for applying linguistic algorithms of patternrecognition for computer understanding of image semantic content in intelligent information systems. A successful obtaining of the crucial semantic information of the image - especially medical - may contribute considerably to the creation of new intelligent cognitive information systems. thanks to the new algorithms of cognitive resonance between stream of the data extracted from the image and expectations taken from the representation of the medical knowledge, we can understand the merit content of the image even if the form of the image is very different from any known pattern. It seems that in the near future the technique of automatic understanding of images may become one of the effective tools for semantic interpreting, and intelligent storing of the visual data in scattered databases. In this article we will try proving that structural techniques may be applied in the case of tasks related to automatic classification and machine perception of the semantic meaning of selected classes of medical patterns.
For Pen-input on-line signature verification algorithms, the influence of intersession variability is a considerable problem because hand-written signatures change with time, causing performance degradation. In our pr...
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