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tfidf 余弦短文本求相似度
gensim jieba pandas
Tfidf = Tfidf(stopwords_file="", work_dir="", work_file_prefix="")
#stopwords_file 停用词文件 可不填 包里自带有
#work_dir 工作目录 模型存储的路径，不填则在当前项目根目录下 建议填
#work_file_prefix 文件名字前缀， 不填则训练的模型名字为 _.model 可以填时间戳，或者用户id，建议填写 不然模型会相互覆盖
# QA 场景
# 问题列表
question_list = [
"test1-question","test2-question","test3-question"
]
# 答案列表
answer_list = [
"test1-answer","test2-answer","test3-answer"
]
Tfidf = Tfidf(stopwords_file="", work_dir="", work_file_prefix="")
# 训练模型并保存
Tfidf.save_model(question_list=question_list,answer_list=answer_list)
# 输入问题，并去计算相似度
Tfidf.run(question="test question")
FAQs
My short description for my project.
We found that nlp-tfidf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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