An approach is provided for generating parking restriction data using a machine learning model. The approach involves determining a plurality of classification features associated with a set of labeled road links. Each of the labeled road links is labeled with a parking restriction label that indicates a parking restriction status of said each of the labeled road links. The approach also involves training the machine learning model to classify an unlabeled road link of the geographic database using the plurality of classification features. The approach further involves determining the plurality of classification features for the unlabeled road link. The approach further involves processing the plurality of classification features for the unlabeled road link using the trained machine learning model to associate an assigned parking restriction label to the unlabeled road link. The approach further involves storing the assigned parking restriction label as the parking restriction data.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for generating parking restriction data using a machine learning model, comprising: determining a plurality of classification features associated with a set of labeled road links, wherein each of the labeled road links is labeled with a parking restriction label that indicates a parking restriction status of said each of the labeled road links; training the machine learning model to classify an unlabeled road link of the geographic database using the plurality of classification features; determining the plurality of classification features for the unlabeled road link; processing the plurality of classification features for the unlabeled road link using the trained machine learning model to associate an assigned parking restriction label to the unlabeled road link; and storing the assigned parking restriction label as the parking restriction data. 2. The method of claim 1, wherein the parking restriction label or the assigned parking restriction label includes at least one of a legal parking label indicating that the parking restriction status is legal for at least one time period, an illegal parking label indicating that the parking restriction status is illegal, and a purely legal parking label indicating that parking is always legal. 3. The method of claim 1, wherein the determining of the plurality of classification features comprises querying a geographic database for a functional class feature of said each of the labeled road links, the unlabeled road link, or a combination thereof as at least one of the plurality of classification features. 4. The method of claim 1, wherein the determining of the plurality of classification features comprises: determining probe trace data originating from or terminating at said each of the labeled road links or the unlabeled road link; and calculating a historical parking availability feature based on the determined probe trace data as at least one of the plurality of classification features. 5. The method of claim 4, further comprising: determining the probe trace data and the historical parking availability feature with respect to a plurality of time epochs. 6. The method of claim 5, wherein the historical parking availability feature is an average across the plurality of time epochs. 7. The method of claim 1, wherein at least one of the plurality of classification features corresponds to a number of the plurality of time epochs for which parking availability information is known for said each of the plurality of labeled road links or the unlabeled road link. 8. The method of claim 1, wherein the set of labeled road links are a first portion of a plurality of stored road links in the geographic database that have been manually labeled with the parking restriction label, and the unlabeled road link is included within a second portion of the plurality of stored road links in the geographic database that is not labeled with the parking restriction label. 9. The method of claim 1, further comprising: presenting the assigned parking restriction label in a user interface for managing the geographic database. 10. The method of claim 1, further comprising: presenting a representation of the assigned parking restriction label in a mapping user interface of a user device. 11. An apparatus for generating parking restriction data using a machine learning model, comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine a plurality of classification features associated with a set of labeled road links, wherein each of the labeled road links is labeled with a parking subtype label indicating a subtype of the parking; train the machine learning model to classify an unlabeled road link of the geographic database using the plurality of classification features, wherein the unlabeled road link is unlabeled at least with respect to the parking subtype label; determine the plurality of classification features for the unlabeled road link; process the plurality of classification feature for the unlabeled road link using the trained machine learning model to associate an assigned parking subtype label to the unlabeled road link; and store the assigned parking subtype label as the parking restriction data. 12. The apparatus of claim 11, wherein the parking subtype label or the assigned parking subtype label includes at least one of a free parking label indicating that the parking is legal and has no cost, a permitted parking label indicating that the parking is legal and a parking permit is required, and a paid parking label indicating that the parking is legal and a payment for the parking is required. 13. The apparatus of claim 11, wherein the plurality of classification features includes a functional class of said each of the labeled road links or the unlabeled road link. 14. The apparatus of claim 11, wherein the determining of the plurality of classification features comprises: process probe trace data collated across a plurality of time epochs to determine a historical parking availability feature, a number of epochs with known parking availability feature, or a combination thereof as at least one of the plurality of classification features. 15. The apparatus of claim 11, wherein the plurality of classification features includes one or more characteristics of a point of interest proximate to said each of the labeled road links or the unlabeled road link. 16. The apparatus of claim 11, wherein which features to include in the plurality of classification features is based on a respective location of said each of the labeled road links or the unlabeled road link. 17. A non-transitory computer-readable storage medium for generating parking restriction data using a machine learning model, carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the following steps: querying a geographic database for a set of road links that are unlabeled with respect to a parking restriction label; automatically labeling the set of road links with a respectively assigned parking restriction label using a machine learning model, wherein the machine learning model is trained to classify the set of road links using a plurality of classification features determined from another set of road links that were previously labeled with a known parking restriction label; and storing the respectively assigned parking restriction label in the geographic database as the parking restriction data. 18. The non-transitory computer-readable storage medium of claim 17, wherein the respectively assigned parking restriction label or the known parking restriction label includes at least one of a legal parking label indicating that the parking restriction status is legal for at least one time period, an illegal parking label indicating that the parking restriction status is illegal, and a purely legal parking label indicating that parking is always legal. 19. The non-transitory computer-readable storage medium of claim 17, wherein the plurality of classification features includes a functional class of a road link, a historical parking availability at the road link, an average number of time epochs with parking availability at the road link, or a combination thereof. 20. The non-transitory computer-readable storage medium of claim 17, wherein the apparatus is further caused to perform: presenting the respectively assigned parking restriction label in a user interface for managing the geographic database.