Knowledge Discovery from Large-scale Text Sequences by Integrating Sequential Data Mining and Advanced Reasoning

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In this research, we developed some new fast and effective sequential data-mining technology for the knowledge discovery from series of large-scale text data. We also proposed a new method for structuring and compressing a huge amount of datawhich are extracted in data-mining process. Furthermore, we gave some new algorithms for extracting latent rules in the form of negative association rule mining, and also for discovering missing factors in the form of inductive reasoning. We study these issues not only from a theoretical viewpoint but also from an experimental evaluation.