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公开(公告)号：US20210383279A1
公开(公告)日：2021-12-09
申请号：US17445905
申请日：2021-08-25
Inventor： Weijia ZHANG , Hao LIU , Dejing DOU , Hui XIONG
Abstract: Provided are an intelligent recommendation method and apparatus, a model training method and apparatus, an electronic device, and a storage medium, which relate to artificial intelligence technologies, and are applicable to the intelligent recommendation and the intelligent transportation technologies. The intelligent recommendation method includes: determining an object recommendation request; determining, according to a multi-agent strategy model and the object recommendation request, object execution actions of at least two agent objects matching the object recommendation request; determining a target object execution action according to the object execution actions; and recommending the object recommendation request to a target agent object corresponding to the target object execution action.
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2.发明申请公开(公告)号：US20210042641A1
公开(公告)日：2021-02-11
申请号：US16823214
申请日：2020-03-18
Inventor： Yanyan LI , Jianguo DUAN , Hui XIONG
Abstract: A method, an apparatus and a storage medium for stay point recognition and prediction model training are proposed. The method may include: for a to-be-recognized positioning point, obtaining respectively features of N predetermined dimensions for the to-be-recognized positioning point, N being a positive integer greater than one; generating a feature vector for the to-be-recognized positioning point according to the features obtained; determining whether the to-be-recognized positioning point is a stay point based on the feature vector, by using a prediction model obtained by pre-training. The technical solution may be applied to improve the accuracy and a recall rate of the stay point recognition.
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公开(公告)号：US20210334278A1
公开(公告)日：2021-10-28
申请号：US17110144
申请日：2020-12-02
Inventor： Jingbo ZHOU , Hui XIONG
IPC: G06F16/2458 , G06F16/29 , G06F16/28 , G06F16/901 , G06N3/08 , G06N3/04
Abstract: A method and apparatus for mining a competition relationship between POIs. An embodiment of the method includes: acquiring a graphlet mining result obtained by mining map retrieval data of users which comprises attribute information of retrieved target POIs, the graphlet mining result comprising occurrence frequencies of respective preset situations, and a preset situation comprising: conforming to attribute information of POIs represented by a corresponding preset graphlet and a preset association relationship between attribute information of at least two POIs; for a first and second POI, determining an occurrence frequency of a preset situation corresponding to a preset graphlet where attribute information of the first and second POI co-occur, and generating a relationship feature of the first and second POI; and inputting the relationship feature into a pre-trained relationship prediction model to obtain a competition relationship prediction result of the first POI and the second POI.
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4.发明申请公开(公告)号：US20210224821A1
公开(公告)日：2021-07-22
申请号：US17208671
申请日：2021-03-22
Inventor： Xinjiang Lu , Shangfo Huang , Hui XIONG
Abstract: A land usage property identification method, apparatus, electronic device and storage medium are disclosed. The method includes: acquiring point-of-interest (POI) data and area-of-interest (AOI) data; dividing a target area to be identified according to road network information, and obtaining at least one block in the target area; associating acquired POI data to a corresponding target block in the at least one block; obtaining a first weight set corresponding to a corresponding category of each POI data in the target block; obtaining a second weight set corresponding to a corresponding area of each AOI data in the target block; obtaining a land usage property weight set according to the first weight set, the second weight set and a preset land usage classification standard; and identifying a land usage property of the target block according to a target weight in the land usage property weight set.
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公开(公告)号：US20210356290A1
公开(公告)日：2021-11-18
申请号：US17386302
申请日：2021-07-27
Inventor： Jingbo ZHOU , Hui XIONG
IPC: G01C21/36
Abstract: A method for recommending a point of interest (POI) includes: generating a user explicit feature based on a user profile of a user to be recommended; generating a POI explicit feature based on a POI profile of each candidate POI in a pre-constructed POI hierarchical structure; generating a historical interaction feature based on historical interaction behaviors of the user to be recommended to each candidate POI; determining a matrix of recommending values for each hierarchy based on at least one of the user explicit feature, the POI explicit feature and the historical interaction feature in combination with an association relationship between inter-hierarchy candidate POIs and/or intra-hierarchy candidate POIs in the POI hierarchical structure; and selecting at least one target POI from the candidate POIs of each hierarchy based on the matrix of recommending values for each hierarchy.
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Patent Agency Ranking
公开(公告)号：US20210254992A1
公开(公告)日：2021-08-19
申请号：US17037144
申请日：2020-09-29
Inventor： Jingbo ZHOU , Renjun HU , Airong JIANG , Jianguo DUAN , Hui XIONG
Abstract: 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.
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7.发明申请公开(公告)号：US20210233405A1
公开(公告)日：2021-07-29
申请号：US17024421
申请日：2020-09-17
Inventor： Weijia ZHANG , Hao LIU , Hui XIONG
Abstract: The present disclosure provides a parking lot free parking space predicting method and apparatus etc., and relates to the field of artificial intelligence. The method comprises: building a parking lot association graph and an information propagation graph for parking lots in a region to be processed, each junction in the graphs representing a parking lot, and connecting parking lots meeting a predetermined condition through edges; as for any parking lot i without a real-time sensor, determining local space correlation information of parking lot i according to environment context features of the parking lot i and neighboring parking lots which are in the parking lot association graph and connected to the parking lot i through edges; determining free parking space estimation information of the parking lot i according to free parking space information of neighboring parking lots with real-time sensors in the information propagation graph; determining time correlation information of the parking lot i according to the determined two kinds of information, and predicting future free parking space information of the parking lot i according to the information. The solution of the present disclosure may be applied to improve the accuracy of the prediction result.
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公开(公告)号：US20210390394A1
公开(公告)日：2021-12-16
申请号：US17171507
申请日：2021-02-09
Inventor： Yaqing WANG , Hui XIONG
Abstract: The present disclosure provides a method for generating a recommendation model, a content recommendation method, and a content recommendation apparatus, and an electronic device, and relates to an artificial intelligence field and a deep learning field. The method for generating a recommendation model includes: obtaining a graph training sample set; inputting the graph training sample set into a machine learning model to train the machine learning model, in which the machine learning model includes at least one low-rank graph convolutional network, and the low-rank graph convolutional network includes a complete weight matrix composed of a first low-rank matrix and a second low-rank matrix; in which a training objective of the low-rank graph convolutional network includes a first parameter item, a second parameter item and a non-convex low-rank item; and in responding to detecting that a training end condition is met, determining the machine learning model as a recommendation model.
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公开(公告)号：US20210044930A1
公开(公告)日：2021-02-11
申请号：US16821729
申请日：2020-03-17
Inventor： Yanyan LI , Jianguo DUAN , Hui XIONG
IPC: H04W4/029
Abstract: A method, an apparatus, a computer device and a storage medium for stay point recognition are disclosed. The method comprises: obtaining reference stay points corresponding to a to-be-recognized positioning point; selecting from the reference stay points a stay point in a predetermined relationship with the to-be-recognized positioning point; and determining whether the to-be-recognized positioning point is a stay point based on the stay point selected. The technical solution may improve the accuracy and recall rate of the stay point recognition.
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公开(公告)号：US20200326197A1
公开(公告)日：2020-10-15
申请号：US16710566
申请日：2019-12-11
Inventor： Yanyan LI , Jianguo DUAN , Hui XIONG
IPC: G01C21/34 , G06F16/29 , G06F40/242 , G06N20/00
Abstract: Embodiments of the present disclosure provide a method, apparatus, computer device, and storage medium for determining a POI alias. The method may include: acquiring a to-be-processed target POI, and generating a candidate alias list corresponding to the target POI based on a query behavior-associated log matching the target POI; and screening out at least one target alias corresponding to the target POI in the candidate alias list, according to an association relationship between each candidate alias in the candidate alias list and the target POI.
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