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Web page training method and apparatus, search intention identification method and apparatus

机译:网页训练方法和装置,搜索意图识别方法和装置

摘要

The present disclosure relates to a web page training method and device. The method includes: obtaining a training web page set of a manually annotated class, and generating a web page vector of a web page in the training web page set, specifically including: obtaining an effective history query character string of a first training web page in the training web page set, and performing word segmentation on the effective history query character string; obtaining an effective quantity of times of each segmented word, the effective quantity of times being a total quantity of times the segmented word occurs in the effective history query character string; calculating a segmented word weight of each segmented word according to the effective quantity of times of each segmented word; generating a web page vector of the first training web page according to each segmented word and the corresponding segmented word weight; and generating a web page classification model according to the manually annotated class of the web page in the training web page set and the corresponding web page vector. Training costs are low, efficiency is high, and class annotation may be automatically performed on a web page after the web page classification model is generated, so that an accuracy rate of an identified intention is higher. A search intention identification method and device are further put forward.
机译:本公开涉及一种网页训练方法和装置。该方法包括:获取手动标注类的训练网页集,并在训练网页集中生成网页的网页矢量,具体包括:获取第一训练网页的有效历史查询字符串。训练网页集,对有效历史查询字符串进行分词;获取每个分段词的有效次数,所述有效次数为所述分​​段词在有效历史查询字符串中出现的总次数;根据每个分段词的有效次数计算每个分段词的分段词权重;根据每个分割词和对应的分割词权重,生成第一训练网页的网页矢量;根据训练网页集中的手动标注的网页类别和对应的网页矢量,生成网页分类模型。训练成本低,效率高,并且在生成网页分类模型后可以在网页上自动进行类别标注,从而提高了识别意图的准确率。进一步提出了一种搜索意图识别方法和装置。

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