• Publications
  • Influence
Efficient time series matching by wavelets
  • K. Chan, A. Fu
  • Computer Science
  • Proceedings 15th International Conference on Data…
  • 23 March 1999
Time series stored as feature vectors can be indexed by multidimensional index trees like R-Trees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to timeExpand
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HOT SAX: efficiently finding the most unusual time series subsequence
In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the rest of the timeExpand
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Entropy-based subspace clustering for mining numerical data
Mining numerical data is a relatively difficult problem in data mining. Clustering is one of the techniques. We consider a database with numerical attributes, in which each transaction is viewed as aExpand
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Utility-based anonymization using local recoding
Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has attracted much research work. Most of the previous methods use globalExpand
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Anonymizing transaction databases for publication
This paper considers the problem of publishing "transaction data" for research purposes. Each transaction is an arbitrary set of items chosen from a large universe. Detailed transaction data providesExpand
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Mining association rules with weighted items
Discovery of association rules has been found useful in many applications. In previous work, all items in a basket database are treated uniformly. We generalize this to the case where items are givenExpand
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(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that aExpand
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A fast distributed algorithm for mining association rules
With the existence of many large transaction databases, the huge amounts of data, the high scalability of distributed systems, and the easy partitioning and distribution of a centralized database, itExpand
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Enhancing Effectiveness of Outlier Detections for Low Density Patterns
Outlier detection is concerned with discovering exceptional behaviors of objects in data sets.It is becoming a growingly useful tool in applications such as credit card fraud detection, discoveringExpand
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K-isomorphism: privacy preserving network publication against structural attacks
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due to the diversity andExpand
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