11. A mobility pattern mining method, comprising: collecting a user's historical data; obtaining stay points of the user from the historical data; obtaining a semantic tree for a certain topic and extracting topic related stay points from the stay points of the user by using the semantic tree for the certain topic; determining a candidate mobility pattern of the user based on the topic related stay points; and selecting a frequent mobility pattern which matches the candidate mobility pattern of the user best from a frequent mobility pattern database related to the certain topic; wherein the frequent mobility pattern database is set in advance based on historical data for a plurality of users.
11. A mobility pattern mining method, comprising: collecting a user's historical data; obtaining stay points of the user from the historical data; obtaining a semantic tree for a certain topic and extracting topic related stay points from the stay points of the user by using the semantic tree for the certain topic; determining a candidate mobility pattern of the user based on the topic related stay points; and selecting a frequent mobility pattern which matches the candidate mobility pattern of the user best from a frequent mobility pattern database related to the certain topic; wherein the frequent mobility pattern database is set in advance based on historical data for a plurality of users. 14. The mobility pattern mining method according to claim 11 , wherein a sub tree of the semantic tree for the certain topic is combined with the topic related stay points as leaf nodes to form the candidate mobility pattern of the user.