哈里:测量弦相似度的工具

Konrad Rieck, Christian Wressnegger
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引用次数: 17

摘要

比较字符串并评估它们的相似性是机器学习许多应用领域的基本操作,如信息检索、自然语言处理和生物信息学。从业者可以从大量可用的相似性度量中进行选择,每个度量都强调字符串数据的不同方面。在本文中,我们介绍Harry,一个专门用于测量字符串相似性的小工具。Harry实现了20多种相似性度量,包括常见的字符串距离和字符串核,如Levenshtein距离和子序列核。该工具在设计时考虑了效率,支持多线程和分布式计算,支持对大型字符串数据集的分析。Harry支持常见的数据格式,因此可以与分析环境,如Matlab, Pylab和Weka接口。
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Harry: A Tool for Measuring String Similarity
Comparing strings and assessing their similarity is a basic operation in many application domains of machine learning, such as in information retrieval, natural language processing and bioinformatics. The practitioner can choose from a large variety of available similarity measures for this task, each emphasizing different aspects of the string data. In this article, we present Harry, a small tool specifically designed for measuring the similarity of strings. Harry implements over 20 similarity measures, including common string distances and string kernels, such as the Levenshtein distance and the Subsequence kernel. The tool has been designed with efficiency in mind and allows for multi-threaded as well as distributed computing, enabling the analysis of large data sets of strings. Harry supports common data formats and thus can interface with analysis environments, such as Matlab, Pylab and Weka.
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