Beijing Baidu Netcom Science and Technology Co., Ltd.

Guyue Zhou

Jingzhou He

Zhihong Fu

Jinbo Zhan

Qiugen Xiao

Liqun Zheng

Chao Zhou

Shuo Huang

Shiwei Huang

Jiaxin Lin

Lei Shi

Yan Zhang

Rui Chen

Di Jiang

Guang Ling

Wei Bi

Yuhui Cao

Zhisheng Wang

Tixi He

Yingbin Su

Zhihui Liu

A news interaction method, apparatus, device and computer storage medium are proposed. Input information input by a user upon reading current news content is obtained; parsing information of the input information is obtained based on the current news content, where the parsing information includes intent information of the input information; the input information is distributed to at least one news interactive service subsystem according to the intent information of the input information, and a return result returned by the at least one news interactive service subsystem is received; and a display result is selected from the return result according to a preset policy, and provided to the user.

News interaction method, apparatus, device and computer storage medium

The present disclosure provides a method and an apparatus for providing information based on artificial intelligence. The method includes: determining a characteristic of interest of the user according to historical access records of the user; and displaying an information card matched with the characteristic of interest in an information displaying interface, the information card including core contents of news matched with the characteristic of interest determined by analyzing news in a database.

Method and apparatus for providing information based on artificial intelligence

Embodiments of the present disclosure disclose a method for modifying a segmentation model based on artificial intelligence, a device and a storage medium. The method may include: acquiring a model parameter of the segmentation model, and performing a training on a feature vector corresponding to a preset generalized feature of a first training corpus via a neural network so as to acquire a model parameter of the preset generalized feature; performing a word segmentation on the first training corpus according to the model parameter of the segmentation model and the model parameter of the preset generalized feature, so as to acquire a segmentation result; and comparing the segmentation result with the first training corpus according to a preset rule, and modifying the model parameter of the segmentation model and a parameter of the neural network according to a comparison result.

Method for modifying segmentation model based on artificial intelligence, device and storage medium

Embodiments of the present disclosure disclose a word segmentation method based on artificial intelligence, a server and a storage medium. The word segmentation method may include: acquiring a corpus to be segmented and a segmentation model corresponding to a preset segmentation template; matching the corpus to be segmented with the segmentation model according to a preset matching algorithm, and acquiring a target phrase satisfying a first preset rule in the corpus to be segmented; modifying an emission matrix corresponding to the segmentation model and the corpus to be segmented according to the target phrase; and performing a word segmentation on the corpus to be segmented according to the emission matrix modified, to acquire a first segmentation result.

Word segmentation method based on artificial intelligence, server and storage medium

Embodiments of the present disclosure disclose a method and an apparatus for customizing a word segmentation model based on artificial intelligence, a device and a medium. The method includes the followings. A customized segmentation training corpus is acquired. A first preset word segmentation model is rectified with an increment training method or a weight intervention method, based on the customized segmentation training corpus, to obtain a customized word segmentation model corresponding to the customized segmentation training corpus.

Method and apparatus for customizing word segmentation model based on artificial intelligence, device and medium

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Beijing, China

Guyue Zhou