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Size: 73728 |
Author: 小青 |
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Description: JAVA实现文本聚类，用到TF/IDF权重，用余弦夹角计算文本相似度，用k-means进行数据聚类等数学和统计 知识。-JAVA realization of text clustering, using TF/IDF weight, calculated using cosine angle between the text of similarity, using k-means clustering for data such as mathematical and statistical knowledge.
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Size: 1024 |
Author: 优优 |
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Description: tf-idf 算法对文章进行词汇统计,包括各个词的权值，出现次数等-tf-idf algorithm vocabulary statistics articles, including the right of the value of each word, frequency, etc.
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Size: 66560 |
Author: gujun |
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Description: tf-idf算法代码的一个实现，简单的小程序-tf-idf algorithm for an implementation of the code, a simple applet
Platform: |
Size: 240640 |
Author: longhorn1987 |
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Description: TF (Term Frequency)/IDF (Inverse Document Frequency) 搜索算法的JAVA实现-TF/IDF algorithm in JAVA
Platform: |
Size: 36864 |
Author: angus |
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Description: simple TF-IDF Algorithm for text mining
Platform: |
Size: 1817600 |
Author: LadyHacker |
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Description: 实现了中文分词，我还自己加入了if-idf和聚类。-Achieve a Chinese word, I myself joined the if-idf and clustering.
Platform: |
Size: 9366528 |
Author: liu |
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Description: Using TF-IDF to Determine Word Relevance in Document Queries :
In this paper, we examine the results of applying
Term Frequency Inverse Document Frequency
(TF-IDF) to determine what words in a corpus of
documents might be more favorable to use in a
query. As the term implies, TF-IDF calculates
values for each word in a document through an
inverse proportion of the frequency of the word
in a particular document to the percentage of
documents the word appears in. Words with
high TF-IDF numbers imply a strong
relationship with the document they appear in,
suggesting that if that word were to appear in a
query, the document could be of interest to the
user. We provide evidence that this simple
algorithm efficiently categorizes relevant words
that can enhance query retri
Platform: |
Size: 156672 |
Author: muhammad |
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