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新词发现算法(New Word Detection)

与 NCXavier 原本 repo 的区别 (Difference with the original fork):

  1. 更新至python3 (Updated to python 3)
  2. 针对原本就带 空格/符号/拆分符号 的语料做一些优化 (Optimize for corpus with space/split symbol)
  3. 优化左右熵(自由度),将左右邻接字从 list 改为 set (Optimize data format of entropy)

参考:
Reference:

代码说明:
Code describing:

  • extract.py:
    提供文档中所有成词的可能组合,以及计算词的点互信息时的一个组合。
    Providing all possible word combines in document, and computing all word combines of PMI.
  • entropy.py:
    计算左右邻居熵的大小
    Computing left and right entropy of neighbors
  • wordseg.py:
    根据计算出的频数、点互信息和左右熵来找出成词可能的组合,最后与词典对比找出新词。
    Finding all possible word combines by frequency, PMI and left/right entropy of neighbors, then comparing with diction to detect new word.

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新词发现算法(NewWordDetection)

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