Determining attribute information of geographical locations

1. A computer-implemented method comprising:

obtaining, at a terminal device, a plurality of attribute features associated with a geographical location, wherein the plurality of attribute features are determined based on geographical and residential information data of the geographical location that is collected from one or more remote devices;

determining, for each particular attribute feature, a score value and a weight value of the particular attribute feature, wherein the weight value of the particular attribute feature is determined using an integrity weight value and an authenticity weight value, wherein the authenticity weight value is determined by comparing keywords in two or more attribute features based on a natural language similarity determining algorithm, wherein the integrity weight value is determined by comparing a pre-estimated consumption amount of an estimated population of the geographic location with an actual consumption amount of an actual population of the geographic location obtained from a payment server, the pre-estimated consumption amount of the estimated population having been determined prior to the actual consumption amount of the actual population obtained from the payment server;

calculating an attribute value for the geographical location that corresponds to the particular attribute feature using the score value and the weight value corresponding to the particular attribute feature;

providing, by the terminal device and to a navigation server, the attribute value for the geographical location;

receiving, by the terminal device and from the navigation server, an electronic map that includes the geographical location; and

displaying, by the terminal device, the attribute value on the electronic map with respect to the geographical location.

2. The computer-implemented method of claim 1 , wherein the score value of the particular attribute feature is determined based on a result of a comparison of the particular attribute feature of the geographical location with a corresponding attribute feature of another geographical location.

3. The computer-implemented method of claim 1 , wherein the weight value of the particular attribute feature is further determined using the integrity weight value, the authenticity weight value, and an importance weight value of the particular attribute feature.

4. The computer-implemented method of claim 1 , wherein calculating the attribute value for the geographical location comprises:

obtaining the attribute value as an output of a pre-trained algorithm model, wherein inputs of the pre-trained algorithm model are the plurality of attribute features; or

performing a weighting calculation based on the score value and the weight value corresponding to the particular attribute feature.

5. The computer-implemented method of claim 1 , wherein the attribute value is calculated using a predetermined calculation method.

6. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

obtaining, at a terminal device, a plurality of attribute features associated with a geographical location, wherein the plurality of attribute features are determined based on geographical and residential information data of the geographical location that is collected from one or more remote devices;

determining, for each particular attribute feature, a score value and a weight value of the particular attribute feature, wherein the weight value of the particular attribute feature is determined using an integrity weight value and an authenticity weight value, wherein the authenticity weight value is determined by comparing keywords in two or more attribute features based on a natural language similarity determining algorithm, wherein the integrity weight value is determined by comparing a pre-estimated consumption amount of an estimated population of the geographic location with an actual consumption amount of an actual population of the geographic location obtained from a payment server, the pre-estimated consumption amount of the estimated population having been determined prior to the actual consumption amount of the actual population obtained from the payment server;

calculating an attribute value for the geographical location that corresponds to the particular attribute feature using the score value and the weight value corresponding to the particular attribute feature;

providing, by the terminal device and to a navigation server, the attribute value for the geographical location;

receiving, by the terminal device and from the navigation server, an electronic map that includes the geographical location; and

displaying, by the terminal device, the attribute value on the electronic map with respect to the geographical location.

7. The non-transitory, computer-readable medium of claim 6 , wherein the score value of the particular attribute feature is determined based on a result of a comparison of the particular attribute feature of the geographical location with a corresponding attribute feature of another geographical location.

8. The non-transitory, computer-readable medium of claim 6 , wherein the weight value of the particular attribute feature is further determined using the integrity weight value, the authenticity weight value, and an importance weight value of the particular attribute feature.

9. The non-transitory, computer-readable medium of claim 6 , wherein calculating the attribute value for the geographical location comprises:

obtaining the attribute value as an output of a pre-trained algorithm model, wherein inputs of the pre-trained algorithm model are the plurality of attribute features; or

performing a weighting calculation based on the score value and the weight value corresponding to the particular attribute feature.

10. The non-transitory, computer-readable medium of claim 6 , wherein the attribute value is calculated using a predetermined calculation method.

11. A computer-implemented system, comprising:

one or more computers; and

one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:

obtaining, at a terminal device, a plurality of attribute features associated with a geographical location, wherein the plurality of attribute features are determined based on geographical and residential information data of the geographical location that is collected from one or more remote devices;

determining, for each particular attribute feature, a score value and a weight value of the particular attribute feature, wherein the weight value of the particular attribute feature is determined using an integrity weight value and an authenticity weight value, wherein the authenticity weight value is determined by comparing keywords in two or more attribute features based on a natural language similarity determining algorithm, wherein the integrity weight value is determined by comparing a pre-estimated consumption amount of an estimated population of the geographic location with an actual consumption amount of an actual population of the geographic location obtained from a payment server, the pre-estimated consumption amount of the estimated population having been determined prior to the actual consumption amount of the actual population obtained from the payment server;

calculating an attribute value for the geographical location that corresponds to the particular attribute feature using the score value and the weight value corresponding to the particular attribute feature;

providing, by the terminal device and to a navigation server, the attribute value for the geographical location;

receiving, by the terminal device and from the navigation server, an electronic map that includes the geographical location; and

displaying, by the terminal device, the attribute value on the electronic map with respect to the geographical location.

12. The computer-implemented system of claim 11 , wherein the score value of the particular attribute feature is determined based on a result of a comparison of the particular attribute feature of the geographical location with a corresponding attribute feature of another geographical location.

13. The computer-implemented system of claim 11 , wherein the weight value of the particular attribute feature is further determined using the integrity weight value, the authenticity weight value, and an importance weight value of the particular attribute feature.

14. The computer-implemented system of claim 11 , wherein calculating the attribute value for the geographical location comprises:

obtaining the attribute value as an output of a pre-trained algorithm model, wherein inputs of the pre-trained algorithm model are the plurality of attribute features; or

performing a weighting calculation based on the score value and the weight value corresponding to the particular attribute feature.

15. The computer-implemented system of claim 11 , wherein the attribute value is calculated using a predetermined calculation method.

16. The computer-implemented method of claim 3 , wherein the weight value of the particular attribute feature corresponds to a commercial value of the geographical location.

17. The non-transitory, computer-readable medium of claim 8 , wherein the weight value of the particular attribute feature corresponds to a commercial value of the geographical location.

18. The computer-implemented system of claim 13 , wherein the weight value of the particular attribute feature corresponds to a commercial value of the geographical location.