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第三届魔镜杯 智能客服问题相似性算法设计 第12名解决方案

Python 100.00%
graph lstm nlp

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question-pairs-matching's Issues

想问下手工特征在哪里下载呀，谢谢

train_features = pd.read_csv('features/0714_all_train_features_17.csv')
test_features = pd.read_csv('features/0714_all_test_features_17.csv')

train_moka_features = pd.read_csv('features/non_nlp_features_train.csv')
test_moka_features = pd.read_csv('features/non_nlp_features_test.csv')
这几个特征是自己加工吗，看代码里并没有提供，谢谢啦

graph feature

请问图特征你们是直接修改预测结果，还是作为一个特征加入训练模型

很受启发，谢谢

你好，我在复现的过程中遇到了一些问题，想向楼主请教一下。就是在特征工程中的powerful_words_oside_tag（）函数中，pword代表的是 sorted_words_power 吗？然后thresh_num和thresh_rate的取值问题。谢谢楼主啦

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