초록 ▼

Automatic map generation is enabled by assigning priorities to each city in a list of cities under consideration for display on a map. A mapping engine determines a reference count for each city, indicating how frequently the city appears in one or more corpora of documents. Based on the reference c

Automatic map generation is enabled by assigning priorities to each city in a list of cities under consideration for display on a map. A mapping engine determines a reference count for each city, indicating how frequently the city appears in one or more corpora of documents. Based on the reference count, and optionally upon other data such as population and political importance, a priority score is assigned to each city. Each city is then assigned to one of a plurality of categories according to the city's priority score. A map is then generated including cities from a specified highest number of categories. In one embodiment, cities from a higher-scored category are presented in a more significant way, e.g., in capital letters, bold type, etc., than are those in the next-highest scored category.

대표청구항 ▼

1. A computer-implemented method for automatically generating a map, the method comprising: determining, by a computer, a frequency with which each of a plurality of city names occurs in a corpus of documents;associating, by the computer, each city name with one of a plurality of city categories acc

1. A computer-implemented method for automatically generating a map, the method comprising: determining, by a computer, a frequency with which each of a plurality of city names occurs in a corpus of documents;associating, by the computer, each city name with one of a plurality of city categories according to the determined frequency of the city name in the corpus; andgenerating, by the computer a digital map including the city names, wherein an appearance of each city name on the map is determined by the category with which it is associated. 2. The computer-implemented method of claim 1 wherein the appearance on the map of city names associated with a first category is larger than the appearance on the map of city names associated with a second category. 3. The computer-implemented method of claim 2 wherein cities associated with the first category have a population greater than cities associated with the second category. 4. The computer-implemented method of claim 1 wherein the corpus of documents includes a set of web pages indexed by a search engine. 5. The computer-implemented method of claim 4 wherein the frequency of the city name in the corpus is the number of web pages that include the city name. 6. The computer-implemented method of claim 4 wherein the frequency of the city name in the corpus is the number of occurrences of the city name in the set of web pages. 7. The computer-implemented method of claim 1 wherein the corpus of documents includes a set of news stories. 8. The computer-implemented method of claim 1 further comprising: determining a population of the city identified by each city name; andwherein associating each city name with the city category further includes associating each city name with the category according to the determined frequency of the city name in the corpus and the population of the identified city. 9. A system for automatically generating a map, the system comprising: a processor;a map source data module, executed by the processor, including a list of city names to be identified on a map; anda mapping engine, executed by the processor, for: associating each city name with a city category according to a determined frequency with which the city name occurs in a corpus of documents; andgenerating a map including the city names, wherein an appearance of each city name on the map is determined by the category with which it is associated. 10. A computer program product for automatically generating a map, the computer program product stored on a computer-readable storage medium and including executable program code configured to cause a processor to carry out the steps of: determining a frequency with which each of a plurality of city names occurs in a corpus of documents;associating each city name with a city category according to the determined frequency of the city name in the corpus; andgenerating a map including the city names, wherein an appearance of each city name on the map is determined by the category with which it is associated. 11. A method for labeling objects on a digital map, the method comprising: determining, by a computer, a reference count for each of the objects with respect to a corpus of documents, the reference count indicating a frequency with which the object appears in the corpus;associating, by the computer, a priority with each of the objects according to the reference count for the object; andrendering, by the computer, a digital map including at least some of the objects, each object including a label, the label having an appearance reflecting the priority associated with the labeled object. 12. The method of claim 11 wherein a first object having a first priority includes a label having a bold appearance, and a second object having a second priority lower than the first priority includes a label not having a bold appearance. 13. The method of claim 11 wherein each object is a city. 14. The method of claim 11 wherein each object is a county. 15. The method of claim 11 wherein each object is an airport. 16. A method for labeling cities on a digital map, the method comprising: determining, by a computer, a priority score for each of a plurality of cities, the priority score determined according to a frequency with which the city appears in a corpus of documents;categorizing each city, by the computer, according to its determined priority score; andrendering, by the computer, a digital map including at least some of the cities, each included city having a label with an appearance determined at least in part by the category to which the city belongs. 17. The method of claim 16 wherein cities having a priority score lower than a threshold amount are not included in the rendered map. 18. The method of claim 17 wherein the threshold is variable according to input from a user. 19. The method of claim 16 wherein the documents in the corpus are web pages. 20. The method of claim 16 wherein the documents in the corpus are customer records, each customer record including a city in which the customer is located. 21. The method of claim 16 wherein determining the priority score for a city further comprises weighting the frequency with which the city appears in the corpus according to a population of the city. 22. The method of claim 16 wherein each document in the corpus has an age, and determining the priority score for a city further comprises weighting the score according to the age of the documents in which the city occurs. 23. The method of claim 16 wherein the corpus includes queries to a search engine. 24. The method of claim 16 in which each document in the corpus is written in the same language.