TOPIC ISLANDS—a wavelet-based text visualization system
Proceedings of the conference on Visualization '98
Machine Learning
Modern Information Retrieval
IEEE Computational Science & Engineering
A survey on wavelet applications in data mining
ACM SIGKDD Explorations Newsletter
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Fast Detection of XML Structural Similarity
IEEE Transactions on Knowledge and Data Engineering
An analysis of the relative hardness of Reuters-21578 subsets: Research Articles
Journal of the American Society for Information Science and Technology
On the Use of Wavelet Decomposition for String Classification
Data Mining and Knowledge Discovery
A novel document retrieval method using the discrete wavelet transform
ACM Transactions on Information Systems (TOIS)
On Textual Documents Classification Using Fourier Domain Scoring
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
The wavelet transform, time-frequency localization and signal analysis
IEEE Transactions on Information Theory
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Currently, Fourier and cosine discrete transformations are used to classify documents. This article proposes a new strategy that uses wavelets in the representation and reduction of data text. Wavelets have been extensively used for dimensionality reduction in the field of signal processing. In this work, we show that a text document, after being subjected to a simple process of reorganization of its terms, can be treated like a signal and analyzed by signal processing tools. We demonstrate that this new representation is able to describe the most relevant features of documents in a synthetic representation and this new perspective improves the performance of the classification algorithm.