Abstract: Methods and apparatuses for assessing user interest scores of users of a mobile network are provided. A method includes for each of a plurality of users (A) determining initial interest scores corresponding to user's interests and interest scores of friends of the user for the user's interests, based on browsing information, and (B) assessing user's interest scores based on the initial interest scores, the interest scores of the friends and friends' influence. The method further includes outputting a list including a subset of the users selected based on the user's interest scores.

Abstract: A method for improving performance of a network includes identifying at least two communities of users within the network, analysing a structure of each community and clustering the communities according to community performance. The method further includes comparing a structure of a lower performing community with a structure of a higher performing community, and changing the structure of the lower performing community substantially to resemble the structure of the higher performing community. Related computer program product for carrying out a method of introducing connections among users of a network and an apparatus configured to introduce connections among users in a network are disclosed.

Abstract: A method is disclosed wherein churn scores and influence scores for each customer in a particular set of customers (the set may include all customers of the network or some subset of all the customers) is determined. Each customer in the set can be ranked based on the customer's churn score and influence score. For example, a customer with a low churn score and a low influence score would be ranked lower than a customer with a high churn score and a high influence score. The customers that are ranked the highest should be the target of a retention campaign on a timely manner.

Abstract: A mobile recommendation system for providing one or more recommendations to a group of mobile users having specific behavior characteristics among a plurality of mobile users is disclosed. The mobile recommendation system comprises of a pre-clustered repository that is configured to store pre-cluster data of the group of mobile users. The mobile recommendation system further comprises a processor capable of controlling a mobile identification generation module that is configured to create a plurality of pre-clusters of mobile users with regard to the pre-cluster data stored in the pre-clustered repository and to generate a unique identification parameter for each mobile user for identifying a priority of the specific behavior characteristics of the respective mobile user in the respective precluster.

Abstract: Methods and apparatuses for assessing user interest scores of users of a mobile network are provided. A method includes for each of a plurality of users (A) determining initial interest scores corresponding to user's interests and interest scores of friends of the user for the user's interests, based on browsing information, and (B) assessing user's interest scores based on the initial interest scores, the interest scores of the friends and friends' influence. The method further includes outputting a list including a subset of the users selected based on the user's interest scores.

Abstract: In one particular aspect a method for categorizing a user of a communication service as a churner or non-churner is provided. In some embodiments, the method includes obtaining call data for the user. Next, the call data is used to determine a value (v1) for a graph parameter for the user, the graph parameter being one of: (a) an out-degree parameter, (b) a Shapley Value parameter, (c) a proximity prestige parameter, and (d) closeness centrality parameter. Next, the determined value (v1) is used to determine a churn value (cv). The churn value (cv) is then used to categorize the user as a churner or a non-churner.

Abstract: Methods of identifying user communities in a telecommunication network include extracting fields from communication records that contain data regarding communications of users of the telecommunication network, generating a plurality of nodes corresponding to users of the telecommunication network based on the extracted fields, determining similarities between pairs of nodes using a similarity metric that measures relationships between the users of the telecommunication network, and grouping the plurality of nodes into non-overlapping communities based on the determined similarities. Related systems and computer program products are also disclosed.

Abstract: An operator's terminal (2) determines a churn risk value associated with a first UE (User Equipment) belonging to a group of operator-connected UEs of a telecommunication system, each UE of the group associated with an initial churn risk value, which depends on the usage. Further, direct weight factors are determined (51) for each direct connection to the first UE, and linked weight factors are determined (52) for each non-direct connection, the weight factors indicating the connectivity between the UEs. Then, the churn risk value is determined (54) based on the initial churn risk values and said weight factors.

Abstract: A method and arrangement in a segmentation manager (200, 600) for forming segments of customers in a communications network for use when offering services to customers jointly in those segments. In the segmentation manager, data relating to the customers' service usage and websites browsed by the customers is collected (500) and subject domains associated to the browsed websites are identified (502). A browsing behaviour of each customer is also determined (504) based on their browsed websites and associated subject domains, and domain interests of each customer are determined (506) based on their browsing behaviour. At least one customer segment is then assigned (508) to each customer based on his/her service usage and domain interests.

Abstract: Exemplary embodiments described herein permit classification of a new mobile user in a communication network based on demographics associated with the new mobile user. The demographics may include all or any of age, income, occupation, frequency of mobile usage, time of mobile usage, and type of mobile usage associated with the mobile users. In an exemplary implementations described herein, the method of classification may include representing, for a sample set of mobile users, each mobile user by a node and mobile usage between two nodes by an edge connecting the two nodes. The method may further include forming one or more communities of nodes based on increasing modularity. Modularity is a measure of how closely two nodes or communities are connected. The method also includes identifying a plurality of subunits by splitting each of the one or more communities based on articulation point determination.

Abstract: A method for identification of an instable network operator service (NOS) plan having one or more mobile users. Instable NOS plans are determined by first determining a heterogeneity constant for each of a plurality of NOS plans. Based at least in part on the constant, the NOS plans are classified among different categories, wherein at least one category identifies an instable NOS plan. For each of the mobile users subscribed to at least one of the instable NOS plan category, determining a best NOS plan from amongst the plurality of NOS plans and a sample network operator service plan based at least in part on a spending behavior of the respective ones of the mobile users. Identifying, the instable NOS plan from amongst the plurality of NOS plans in which maximum number of mobile users correspond to the sample NOS plan as the correspondingly determined best NOS plan.