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SCALABLE STRING MATCHING AS A COMPONENT FOR UNSUPERVISED LEARNING IN SEMANTIC META-MODEL DEVELOPMENT
SCALABLE STRING MATCHING AS A COMPONENT FOR UNSUPERVISED LEARNING IN SEMANTIC META-MODEL DEVELOPMENT
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机译:可伸缩的字符串匹配是语义元模型开发中无监督学习的组件
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摘要
A string analysis tool for calculating a similarity metric between a source string and a plurality of target strings. The string analysis tool may include optimizations that may reduce the number of calculations to be carried out when calculating the similarity metric for large volumes of data. In this regard, the string analysis tool may represent strings as features. As such, analysis may be performed relative to features (e.g., of either the source string or plurality of target strings) such that features from the strings may be eliminated from consideration when identifying target strings for which a similarity metric is to be calculated. The elimination of features may be based on a minimum similarity metric threshold, wherein features that are incapable of contributing to a similarity metric above the minimum similarity metric threshold are eliminated from consideration.
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