JaTeCS是一个开源的JAVA文本分类系统
JaTeCS an open-source JAva TExt Categorization System
摘要：
JaTeCS是一个开源的Java库，支持自动文本分类和其他相关问题的研究，如有序回归和量化，这些问题在意见挖掘应用中特别重要。它涵盖了实验活动的所有步骤，从阅读语料到评估实验结果。由于JaTeCS专注于将文本作为主要输入数据，因此它为用户提供了许多文本专用工具，例如：包括最常用的文本语料库和词汇资源的许多格式的数据读取器、自然语言处理工具、多语言支持、用于特征选择和加权的方法、许多机器学习算法的实现以及用于公知的外部软件的包装器（例如，SVM_light），使其能够从代码中进行完全控制。JaTeCS通过接口抽象了文本处理任务中使用的许多典型工具和过程，从而支持其扩展。该库还提供了一些典型实验设置的“模板”实现（例如，训练测试、k折验证、网格搜索优化、随机运行），其仅通过将模板与数据读取器、学习算法和评估措施连接就能够快速实现实验。
英文摘要：
JaTeCS is an open source Java library that supports research on automatic text categorization and other related problems, such as ordinal regression and quantification, which are of special interest in opinion mining applications. It covers all the steps of an experimental activity, from reading the corpus to the evaluation of the experimental results. As JaTeCS is focused on text as the main input data, it provides the user with many text-dedicated tools, e.g.: data readers for many formats, including the most commonly used text corpora and lexical resources, natural language processing tools, multi-language support, methods for feature selection and weighting, the implementation of many machine learning algorithms as well as wrappers for well-known external software (e.g., SVM_light) which enable their full control from code. JaTeCS support its expansion by abstracting through interfaces many of the typical tools and procedures used in text processing tasks. The library also provides a number of "template" implementations of typical experimental setups (e.g., train-test, k-fold validation, grid-search optimization, randomized runs) which enable fast realization of experiments just by connecting the templates with data readers, learning algorithms and evaluation measures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
