Advances in intelligent data analysis IX

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The annotation outlines various contributions presented at the IDA Symposium, reflecting a shift in focus. Key topics include graph identification, intelligent data analysis, and the measurement of computer performance data. Notable papers discuss recursive sequence mining for named entity relations and the integration of citizen-reported and seismically derived earthquake information through social networks. Innovative techniques in detecting leukemia blood cells using cellular automata and heuristic search are highlighted, along with advancements in decision trees and statistical modeling for short hairpin RNA experiments. The annotation also covers InfraWatch, a system for monitoring infrastructural performance, and the use of deterministic finite automata for detecting EEG spikes and seizures. Additional contributions explore bipartite graphs for monitoring cluster transitions, data mining in data centers, and the application of artificial neural networks in assessing drug carcinogenicity. Document mining in neuroscientific publications, similarity kernels for outlier detection, and frameworks for network simplification are also discussed. The symposium emphasizes a data-driven approach to understanding multimodal communication and the use of CAPTCHAs for indexing cultural artifacts.