Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.

Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.

Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.

Abstract: A digital field-induction water-level intelligent sensing system is provided. The digitalized intelligent field-induction field technology is utilized in the sensing system, thus the problem of water scale formation on the water-level sensors when applied in the severe environment and the problem of sensing system failure easily happening in the high temperature and high humidity environment are solved. The application of the field-induction technology enables the sensing system to detect the water level without electrical connection or mechanical connection, thus the problems of the sensor failure or inaccurate water-level detection caused by the water scale formation are avoided.

Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.

Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.

Abstract: A method and system for recommending potential contacts to a target user is provided. A recommendation system identifies users who are related to the target user through no more than a maximum degree of separation. The recommendation system identifies the users by starting with the contacts of the target user and identifying users who are contacts of the target user's contacts, contacts of those contacts, and so on. The recommendation system then ranks the identified users, who are potential contacts for the target user, based on a likelihood that the target user will want to have a direct relationship with the identified users. The recommendation system then presents to the target user a ranking of the users who have not been filtered out.