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自然语言处理(汉语)算法实现,Java语言实现,经过优化,效率很高。主要包括: 1)汉语分词,采用ICTCLAS系统和Lucene+庖丁解牛系统 2)情感倾向性分析,包括基于统计学习的SVM算法,基于情感词典的词语权重算法,给出文档的情感权重和情感倾向 3)文本聚类,包括KMeas算法实现,文档向量建模,以及采用Weka API 库效率比较 4)词语关系网络,包括词语距离计算,构建词语的近似程度,并刻画词语网络图 5)抽象摘要,采用TFIDF计算文档关键词进行摘要和关键字提取 经过部分优化,对于大数据量处理瓶颈的优化
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自然语言处理全集 (298个子文件)
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187363365fd10021e1a1e6f050b03a899a076c 55B
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ae976ec82d1a9884a7fc0614494f53bf92e53f 560B
afafa3a091626caeb72e9865f156fdf7ce07e3 1KB
共 298 条
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资源评论
- who__2017-09-30正在学习,非常感谢!!
- 1891392017-03-15好文章学习了
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