中文分词算法及python代码实现（持续更新中）

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参考链接：
https://blog.csdn.net/lcwdzl/article/details/78493637
https://blog.csdn.net/liu_zhlai/article/details/52125174?spm=1001.2014.3001.5501
代码源码地址：
https://github.com/lankuohsing/Study_NLP

1. 机械分词算法

1.1. 正向最大匹配算法

custom_dict={"南京","南京市","市长","长江","大桥","江大桥",}
input_sentence="南京市长江大桥"
max_word_len=0
for word in custom_dict:
    if len(word)>max_word_len:
        max_word_len=len(word)

if len(input_sentence)0:
        sub_sentence=input_sentence[start:start+temp_len]
        if sub_sentence in custom_dict:
            seg_results.append(sub_sentence)
            start+=temp_len
            break
        else:
            temp_len-=1
    # 没有子串匹配，则单独成词
    if temp_len==0:
        seg_results.append(input_sentence[start:start+1])
        start+=1
print(seg_results)

1.2. 逆向最大匹配算法

custom_dict={"南京","南京市","市长","长江","大桥","江大桥"}
input_sentence="南京市长江大桥"
max_word_len=0
for word in custom_dict:
    if len(word)>max_word_len:
        max_word_len=len(word)

if len(input_sentence)0:
    temp_len=max_word_len
    if end0:
        sub_sentence=input_sentence[end-temp_len:end]
        if sub_sentence in custom_dict:
            seg_results.append(sub_sentence)
            end-=temp_len
            break
        else:
            temp_len-=1
    # 没有子串匹配，则单独成词
    if temp_len==0:
        sub_sentence=input_sentence[end-1:end]
        seg_results.append(sub_sentence)
        end-=1
print(seg_results)