Abstract: A processing system may obtain a customer identifier at a first retail location of a telecommunication network service provider, determine a recency factor of the identifier, obtain an identification of items of interest to the customer, and determine whether the customer has visited a second retail location of the provider within a time period prior to the customer being at the first retail location. The processing system may then apply, to a fraud detection machine learning model, a plurality of factors comprising: a quantity of items of interest, a value of the items, a factor associated with whether the customer has visited the second retail location within the time period, and the recency factor, where the fraud detection machine learning model outputs a fraud indicator value, determine that the fraud indicator value meets a warning threshold and present a warning to a device at the first retail location.

Abstract: An example method performed by a processing system obtaining a first port-in number for a first mobile device from a first mobile communications service provider, wherein the first port-in number is known to be involved in fraudulent activity, constructing a social graph of communications between the first port-in number and a plurality of other numbers associated with a plurality of other communications devices, identifying, by the processing system, a maximal subgraph of the social graph, wherein the maximal subgraph connects the first port-in number and a subset of the plurality of other numbers that includes those of the plurality of other numbers for which a usage metric is below a predefined threshold for a defined period of time prior to the first port-in number being ported into the first mobile communications service provider, and identifying, by the processing system, a potential fraud ring, based on the maximal subgraph.

Abstract: The present invention refers to a method for characterizing a group of users, related among them by their mobile communication data, according to web navigation data. The method comprises: building a social graph from the mobile communication data of a user and his contacts; extracting web navigation data of each user of the social graph; associating to each edge linking two users of the social graph, web navigation data extracted for both two users; obtaining a measure of harmony based on comparing web navigation data of both two users; and providing a set of metrics for the group of users based on the measures of harmony, characterizing the group of users.

Abstract: The invention relates to a method for determining a user profile in relation to certain web content, according to the user's browsing data. The method comprising the following steps: classifying the browsing data according to content categories; extracting a first set of variables from the user's web browsing data for each category; assigning the user a ranking position for each of the categories, and comparing the first set of variables with the same variables of other users; calculating at least one correction factor for the user's ranking position in each category according to one or more time variables extracted from the web browsing data; recalculating the user's ranking position for each category, taking into account the correction factor calculated for each category; and determining the user profile on the basis of the user's ranking position calculated for each category.

Abstract: The method comprises acquiring information from signals exchanged between a user's mobile computing devices and a plurality of Base Transceiver Stations, or BTSs, analyzing said acquired information for determining, over a period of time, the locations of said user's mobile computing device and deduce through a statistical model the points of interest, identifying and labelling at least part of said user's mobile computing device determined locations as points of interest.

Abstract: The invention relates to a method for speech signal analysis, modification and synthesis comprising a phase for the location of analysis windows by means of an iterative process for the determination of the phase of the first sinusoidal component and comparison between the phase value of said component and a predetermined value, a phase for the selection of analysis frames corresponding to an allophone and readjustment of the duration and the fundamental frequency according to certain thresholds and a phase for the generation of synthetic speech from synthesis frames taking the information of the closest analysis frame as spectral information of the synthesis frame and taking as many synthesis frames as periods that the synthetic signal has. The method allows a coherent location of the analysis windows within the periods of the signal and the exact generation of the synthesis instants in a manner synchronous with the fundamental period.

Abstract: It comprises computing values of cognitive and personality indicators of users of a telecom operator by means of machine learning and data mining algorithms from information available in a telecom operator system extracted from Social Network Analysis metrics, Call Detailed Record information and commercial information of said users stored in an operator's Data Warehouse and Customer Relationship Management systems as well as information from previous surveys, or questionnaires, answered by a representative sample of users as an input of said machine learning and said data mining algorithms. The method involves building a complex computer model that infers the values of the psychological dimensions of said users by means of said machine learning and said data mining algorithms to obtain a multi-dimensional vector for each of the users.

Abstract: The invention relates to a method for speech signal analysis, modification and synthesis comprising a phase for the location of analysis windows by means of an iterative process for the determination of the phase of the first sinusoidal component and comparison between the phase value of said component and a predetermined value, a phase for the selection of analysis frames corresponding to an allophone and readjustment of the duration and the fundamental frequency according to certain thresholds and a phase for the generation of synthetic speech from synthesis frames taking the information of the closest analysis frame as spectral information of the synthesis frame and taking as many synthesis frames as periods that the synthetic signal has. The method allows a coherent location of the analysis windows within the periods of the signal and the exact generation of the synthesis instants in a manner synchronous with the fundamental period.