Beijing Baidu Netcom Science and Technology Co., Ltd.

Baidu Online Network Technology (beijing) Co., Ltd.

Renjun Hu

Hui Xiong

Jingbo Zhou

Hao Liu

Ting Li

Jianguo Duan

Airong Jiang

Yanjie Fu

The present disclosure provides a method for optimizing a tag of a point of interest s(POI). The method includes: obtaining first portrait feature data of each POI in a plurality of POIs and second portrait feature data of each tag in a plurality of marked tags corresponding to the plurality of POIs; mapping the first portrait feature data of each POI and the second portrait feature data of each tag to a metric space to obtain a first feature vector of each POI and a second feature vector of each tag; and optimizing at least one marked tag corresponding to a target POI based on a vector similarity between a first feature vector of the target POI and a second feature vector of at least one tag. The present disclosure provides an apparatus for optimizing a tag of a POI, an electronic device and a computer readable medium.

Method and apparatus for optimizing tag of point of interest, electronic device and computer readable medium

Embodiments of the present disclosure provide a method and apparatus for optimizing a tag of a point of interest. The method includes: acquiring a set of points of interest and a set of tags of points of interest in the set of points of interest; generating a point of interest-tag matrix based on the set of points of interest and the set of tags of points of interest in the set of points of interest; extracting a feature of a point of interest-tag in the point of interest-tag matrix; inputting the feature of the point of interest-tag in the point of interest-tag matrix into a pre-trained ternary self-adaptive collaborative learning model, to obtain a point of interest-tag score matrix; and optimizing the set of tags of points of interest in the set of points of interest based on the point of interest-tag score matrix.

Method and apparatus for optimizing tag of point of interest

The present disclosure provides a method and an apparatus for recommending a travel way. The method includes: obtaining historical travel data; determining a plurality of correlations between respective travel ways according to the historical travel data; generating a vector corresponding to each travel way according to the plurality of correlations between respective travel ways; performing learning on an initial vector corresponding to each user and an initial vector corresponding to each starting-and-arrival pair according to the vector corresponding to each travel way and the historical travel data, to obtain a vector corresponding to each user and a vector corresponding to each starting-and-arrival pair; and recommending a travel way according to the vector corresponding to each travel way, the vector corresponding to each user and the vector corresponding to each starting-and-arrival pair.

Method and apparatus for recommending travel way

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Beijing, China

Renjun Hu