Top-Down Mining of Interesting Patterns from Very High Dimensional Data

  title={Top-Down Mining of Interesting Patterns from Very High Dimensional Data},
  author={Hongyan Liu and Jiawei Han and Dong Xin and Zheng Shao},
  journal={22nd International Conference on Data Engineering (ICDE'06)},
Many real world applications deal with transactional data, characterized by a huge number of transactions (tuples) with a small number of dimensions (attributes). However, there are some other applications that involve rather high dimensional data with a small number of tuples. Examples of such applications include bioinformatics, survey-based statistical analysis, text processing, and so on. High dimensional data pose great challenges to most existing data mining algorithms. Although there are… CONTINUE READING

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