Comments (3)
你好,方便把从train.json抽取出的训练集question_train.txt'文件共享一下么。谢谢
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您好,请教下这个word_vec_300.bin 是怎么训练出来的,数据用的什么,谢谢
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背景: 刚接触这个领域,请教老师问题
过程:
对2G多的那个train.json中的fact提取,分词,再用word2vec训练出词向量,结果:1280257个词,4.66G。
我看您训练后的只有1G多,觉得可能和没有去除停用词有关,可能和分词后没有去重有关,去掉停用词后,1440045个词,5.24G,数量不减反增,没想明白为什么。
问:
1)一般情况下对语料分词后要不要去除停用词,如果去掉的话,在用词向量表示文档的时候,会不会丢失语义,比如:导致,由于,传说等词,且数字需不需要去掉,因为日期,电话号码等在某些领域很多,是有意义的。
2)在分词的时候,每读取一行语料,分词,写入词文件,这样势必会产生很多相同的词语,这个时候要不要去重,不知道您是怎么做的。
感谢。
请问那个里面的question.train 文件有吗?我看他们都没有找到
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Related Issues (18)
- word_vec_300.bin这个哪里能拿到啊 HOT 4
- 法务咨询问题分类的分类数据集能分享一下吗
- 请问能告诉下 question_train.txt是怎么来的吗?思路也行 HOT 14
- 贴一个相关的数据集 HOT 1
- 知识图谱的内容没了吗
- 知识图谱构建没有
- 请问能否提供项目环境具体的requirement
- ..
- embedding/word_vec_300.bin
- 如何获得qa_corpus的标准答案?
- 你好,能提供一下 crime_classify 用的语料么? HOT 4
- 执行法务咨询自动问答时报错 HOT 5
- 词向量 HOT 2
- 罪名分类的TXT训练集可以共享一下么。谢谢 HOT 6
- word2Vec HOT 2
- build_qa_database.py插数的时候有个小问题
- 请问本项目用什么开源协议,是否允许别人商用
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