Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
From Gestalt Theory to Image Analysis: A Probabilistic Approach
From Gestalt Theory to Image Analysis: A Probabilistic Approach
Text Mining: Classification, Clustering, and Applications
Text Mining: Classification, Clustering, and Applications
Automatic text summarization and small-world networks
Proceedings of the 11th ACM symposium on Document engineering
Efficient keyword extraction for meaningful document perception
Proceedings of the 11th ACM symposium on Document engineering
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Keyword extraction is a fundamental problem in text data mining and document processing. A large number of document processing applications directly depend on the quality and speed of keyword extraction algorithms. In this article, a novel approach to rapid change detection in data stream. and documents is developed. It is based on ideas from image processing and especially on the Helmholtz Principle from the Gestalt Theory of human perception. Applied to the problem of keywords extraction, it delivers fast and effective tools to identify meaningful keywords using parameter-free methods. We also define a level of meaningfulness of the keywords which can be used to modify the set of keywords depending on application needs.