Method and device for determining resident city, and electronic device
A technique for determining methods, cities, applied in the field of computers
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Embodiment 1
[0024] refer to figure 1 , which shows a flow chart of the steps of a method for determining a resident city, including:
[0025] Step 101, according to the user's characteristic information, the characteristic information of each candidate city, and the user's behavior information in each candidate city, obtain the fitting probability of the user and each candidate city through city probability model prediction.
[0026] Among them, the characteristic information of the user includes but is not limited to: gender, age, occupation, consumption level, income level, and whether or not he is a travel expert.
[0027] The characteristic information of candidate cities includes but is not limited to: city level, whether the city is a tourist city, the number of local users and remote users in the city, and the average daily orders for hotels, travel and transportation.
[0028] The user's behavior information in each candidate city includes, but is not limited to: the number and p...
Embodiment 2
[0041] The embodiment of the present application describes an optional method for determining the resident city from the level of the system architecture.
[0042] refer to figure 2 , which shows a flow chart of specific steps of another method for determining a resident city.
[0043] Step 201, training a city probability model based on the labeled data sample set, each labeled data sample in the labeled data sample set at least includes: user feature information, feature information of candidate cities, and user behavior information in candidate cities.
[0044]Wherein, each data sample in the labeled data sample set has been labeled whether the corresponding city is the resident city of the corresponding user. In practical applications, a field can be added to indicate whether the data sample is a resident city sample or a non-resident city sample. For example, the sample can be marked by the field ResidentCity. When ResidentCity=1, it means that the sample is a resident...
Embodiment 3
[0104] refer to image 3 , which shows a structural diagram of a device for determining a resident city, specifically as follows.
[0105] The probability prediction module 301 is used to obtain the fitting probability of the user and each candidate city through urban probability model prediction according to the characteristic information of the user, the characteristic information of each candidate city, and the behavior information of the user in each candidate city.
[0106] The first probability threshold determination module 302 is configured to determine a first probability threshold according to the fitting probabilities of the user and each candidate city.
[0107] A resident city determining module 303, configured to determine the user's resident city from the candidate cities according to the first probability threshold.
[0108] To sum up, the embodiment of the present invention provides a device for determining a resident city, the device includes: a probability ...
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