模式识别中的逆集

A. Mikhailov, M. Karavay
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引用次数: 0

摘要

无论基于索引的互联网搜索引擎多么高效,索引或数据的逆表示都不是模式识别的主流。模式识别界对索引方法缺乏兴趣的一个原因是由于使用容易产生噪声的测量作为特征,而不是关键字,结果不稳定。本文提出了一种多维数字数据索引方法,为基于精确索引的模式识别系统开辟了一条道路,该系统继承了搜索引擎前辈高效处理大量数据的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inverse Sets in Pattern Recognition
No matter how efficient indexing-based Internet search engines could be, indexing or inverse representations of data, is not in the mainstream of pattern recognition. One reason for a lack of interest in indexing methods on the part of pattern recognition community is instability of results due to a use of noise-prone measurements as features, rather than key words. The paper suggests a multidimensional numerical data indexing method that opens a path to accurate indexing-based pattern recognition systems that inherit from their search engines predecessors the ability to efficiently deal with large amounts of data.
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