Abstract: A method for network resource classification and identifying user interests based on the classification. The method uses a provided hierarchy of categories for classifying network resources, wherein each category is assigned a text item describing the category and the method includes obtaining resource description data collections corresponding to the network resources, and generating, using a semantic correlation algorithm, a category score vector of a network resource by comparing the resource description data collection to the text item assigned to each category in the hierarchy of categories, wherein the category score vector comprises a category score for each category in the hierarchy of categories, wherein the category score is determined based on at least a semantic correlation measure between the resource description data collection and the text item assigned to a corresponding category, wherein the plurality of network resources are classified based at least on the category score.

Abstract: A method for comparing data records, including extracting, by a computer processor, alphanumeric tokens from a plurality of data records, wherein the plurality of data records are generated by a plurality of entities, generating, by the computer processor, a plurality of indexes each referencing an entity of the plurality of entities by at least one of the alphanumeric tokens that is associated with the entity, extracting target alphanumeric tokens from a target data record of a target entity, identifying a candidate entity from the plurality of entities based on the target alphanumeric tokens and a first index of the plurality of indexes, and calculating, by the computer processor, a first score representing a first similarity measure between a candidate data record selected from the plurality of data records that belongs to the candidate entity and the target data record of the target entity.

Abstract: A method for profiling user activity in a mobile network, including extracting user identifiers from application sessions identified from a mobile network, analyzing the application sessions to determine session blocks based on shared IP address and a minimum separation time threshold, extracting a traffic marker from the session blocks based on a user identifier, identifying a first portion of the session blocks based on the user identifier, wherein the first portion is associated with first mobile network activities of a user identified by the user identifier, identifying a second portion of the session blocks based on the traffic marker, wherein the second portion is associated with second mobile network activities of the user, and analyzing the first portion and the second portion to determine a measure of a mobile network activity of the user.

Abstract: A method for user profile matching, including extracting online social network (OSN) user profile tokens from user profiles of one or more OSNs, generate indexes each referencing a user by at least one of the OSN user profile tokens that is associated with the user, extracting target OSN user profile tokens from a target OSN user profile of the one or more OSNs, identifying a candidate user based on the target OSN user profile tokens and at least one of the indexes, calculating a score representing a similarity measure between a candidate OSN user profile selected from the OSN user profiles that belongs to the candidate user and the target OSN user profile of the target user, and storing, in response to the score exceeding a pre-determined threshold, a combination of the target OSN user profile and the candidate OSN user profile as an expanded profile of the target user.