Abstract: System and method for behavioral and contextual data analytics are disclosed. An example computer system to process observational data received from a wireless device includes a memory including machine readable instructions and a processor to execute the instructions to: process the observational data to identify temporally adjacent applications to generate usage metric data, the observational data including application usage data; build a behavior model based on the identified temporally adjacent applications, the behavior model to describe user behavior associated with the wireless device; and apply the behavior model to predict a usage duration of a second application in response to usage of a first application.

Abstract: System and method for behavioral and contextual data analytics are disclosed. An example computer system to process observational data received from a wireless device includes a memory including machine readable instructions and a processor to execute the instructions to: process the observational data to identify temporally adjacent applications to generate usage metric data, the observational data including application usage data; build a behavior model based on the identified temporally adjacent applications, the behavior model to describe user behavior associated with the wireless device; and apply the behavior model to predict a usage duration of a second application in response to usage of a first application.

Abstract: Electronic arrangement comprising a data interface for transferring data with external elements, at least one processor for processing instructions and other data, and memory for storing the instructions and other data, said at least one processor being configured, in accordance with the stored instructions, to obtain at least one predictive user model including one or more demographic characteristics as dependent variables to be predicted and usage statistics of applications as explanatory variables, obtain deterministic usage statistics indicative of digital applications a target user has utilized during a monitoring period, and determine, through utilization of the deterministic usage statistics obtained during the monitoring period as input to the at least one established predictive model, an estimate of said one or more of the demographic characteristics of the target user.

Abstract: Method for supplying data to remotely cultivate a digital content reference library, to be executed by an electronic terminal device capable of visually displaying digital content to a user and communicating with a communications network, comprising establishing, by automatic observation logic, visual characteristics data representing the on-screen appearance of digital content, such as application, shown via a display of the terminal device (406), and transmitting the visual characteristics data to a remote server for updating a digital content reference library thereat linking content identity information with associated visual characteristics data in the received or processed form (408). A compatible method to be executed on the network side is presented as well as related, applicable terminal devices and server arrangements.

Abstract: System for obtaining and analyzing data on online user behavior and other activity having regard to Internet connectable user devices, optionally mobile devices, the system being configured to collect data from a plurality of data sources, wherein the collected data includes at least individual user-level data acquired from user devices and census-level data indicating behavior and demographic characteristics across the entire population of users, active or measured services, with the user-level data being preferably collected using at least one user research panel of controlled constitution, preferably from multiple devices of each participant in the panel, the collected data being indicative of Internet, content, media, application, and/or device usage, organize the obtained user-level and census-level data into a multivalent categorized data set utilizing an ontological metadata schema, determine an electronic deliverable based on an integration of the user-level data and census-level data wherein census-l

Abstract: Electronic arrangement for single-source cross-platform media measurements, comprising a communication interface arranged to receive observation data having regard to and at least partly determined at a plurality of electronic, preferably personal, devices of a number of users, at least one user of said number being associated with multiple devices of said plurality, said multiple devices belonging to mutually different technological platforms including online platforms for providing media exposure and the multiple devices comprising a usage meter to observe selected events indicative of device usage comprising media exposure, wherein the usage meter of at least one of the multiple devices being further arranged to observe user exposure to media on one or more external offline media distribution platforms, and at least one of the multiple devices being arranged to transmit observation data comprising indications of the observations towards the arrangement, at least one electronic database arranged to store th

Abstract: A method (400) for enhancing data integrity in connection with a digital panel study to be performed by an electronic arrangement preferably comprising one or more servers, wherein the method comprises obtaining data (406) having regard to a plurality of panelists, wherein one or more data points associated with each panelist characterize demographic profile, device ownership, device-level behavioral profile and/or occurrences of events or traffic involving one or more electronic devices associated with the panelist, and where there is more and less complete data associated with different panelists in terms of data points, for a certain panelist of said plurality missing a data point, determining (413), based on the obtained data, a number of other panelists that originally have corresponding data point assigned and are otherwise similar to the certain panelist in terms of a number of other data points according to a selected criterion, preferably requiring similar data point values, and completing the missin

Abstract: System and method for behavioral and contextual data analytics are disclosed. An example computer system to process observational data received from a wireless device includes a memory including machine readable instructions and a processor to execute the instructions to: process the observational data to identify temporally adjacent applications to generate usage metric data, the observational data including application usage data; build a behavior model based on the identified temporally adjacent applications, the behavior model to describe user behavior associated with the wireless device; and apply the behavior model to predict a usage duration of a second application in response to usage of a first application.

Abstract: Method for supplying data to remotely cultivate a digital content reference library, to be executed by an electronic terminal device capable of visually displaying digital content to a user and communicating with a communications network, comprising establishing, by automatic observation logic, visual characteristics data representing the on-screen appearance of digital content, such as application, shown via a display of the terminal device (406), and transmitting the visual characteristics data to a remote server for updating a digital content reference library thereat linking content identity information with associated visual characteristics data in the received or processed form (408). A compatible method to be executed on the network side is presented as well as related, applicable terminal devices and server arrangements.

Abstract: The invention concerns an electronic terminal device with a processing device, a display, a user input element, a memory entity for storing the instructions and other data, and a communication interface for transferring data with external entities, configured, to store a number of digital content fingerprints that each correspond to a usage of display content, whereby log data is generated and recorded comprising behavioral data indicative of user engagement with the electronic terminal device, matches between the stored digital content fingerprints and display content are searched for and detected, and indications of such matches are detected stored in the log data, wherein a selected control action is executed concerning the generation and recording of the log data according to a determined usage status of the UI. The invention also concerns a system for collecting and processing data provided by multiple terminals associated with a plurality of users, and related methods.

Abstract: Electronic terminal device including a processing entity for processing instructions and other data, functionally connected user interface entity, a display and user input elements, optionally a keypad or a touch-sensitive arrangement in connection with the display, a memory entity for storing the instructions and data, and a communication interface for transferring data with external entities, configured, in accordance with the instructions, to store data including a number of predetermined fingerprints, each characterizing display usage such as visual objects associated with software entities and potentially shown to the user via the display during execution of the software entity, and log data including behavioral data indicative of user engagement with the UI of the device, the logging incorporating detecting display usage, and storing indication of such detection in the memory, wherein the device is configured to determine the status of the display, and execute the logging according to the determination.

Abstract: Electronic arrangement (112) comprising a data interface (210) for transferring data with external elements, at least one processor (202) for processing instructions and other data, and memory (204) for storing the instructions and other data, said at least one processor being configured, in accordance with the stored instructions, to obtain at least one predictive user model (312,314) including one or more demographic characteristics as dependent variables to be predicted and usage statistics of applications as explanatory variables, obtain deterministic usage (316) statistics indicative of digital applications a target user has utilized during a monitoring period, and determine (318), through utilization of the deterministic usage statistics obtained during the monitoring period as input to the at least one established predictive model, an estimate of said one or more of the demographic characteristics of the target user.

Abstract: A method for estimating the digital audience (102a, 102b, 102c) reached by a digital network (110) on at least one digital platform (104a, 104b, 104c) to be performed by computer equipment (114, 114B), comprising monitoring transactions (105a, 105b, 105c, 106) on said platform in the digital network for a predefined period, wherein the predefined period comprises at least a preliminary period, target period, and post-period, which are temporally sequential, capturing device-related identifiers associated with the observed transactions, wherein the device-related identifier preferably anonymously identifies a device or device user or related application profile, optionally a browser profile, determining, for each captured device-related identifier, whether it was observed at least once during both said preliminary period and said post-period, to extract persistent device-related identifiers from the captured device-related identifiers, and calculating statistics preferably containing aggregate statistics havin

Abstract: Electronic system for obtaining data, via one or more digital devices, on user behavior, digital transactions, and exposure relative to digital content and services, or external exposure and associated events between the user and the environment via sensors attached to digital devices, the system being configured to collect data reflecting the content and objects that the user at least potentially perceives as rendered on one or more digital screens attached to smart devices, reconstruct the at least potentially perceived visual landscape based on the collected data, and determine the target and/or level of user attention in view of the reconstruction and associated exposure events detected therein, and to apply locally stored information about rules or fingerprints in the digital object recognition process involving the collected data and validation of the type or identity of user actions, digital content, or external objects, as reflected by the reconstruction recapturing the visual landscape.

Abstract: Network server arrangement for processing non-parametric, multi-dimensional, spatial and temporal human behavior or technical observations measured pervasively, and related method for the same are disclosed. An example computer system to process usage data received from a wireless device, the computer system including a memory including machine readable instructions; and a processor to execute the instructions to: process the usage data to identify applications which were sequentially accessed on the wireless device in a time period; build a behavior model based on the identified applications, the behavior model to describe user behavior associated with the wireless device; execute the behavior model to predict usage of an application on the wireless device; based on the prediction, monitor usage of the wireless device to determine an accuracy of the prediction; and update the behavior model based on the accuracy of the prediction.

Abstract: Network server arrangement for processing non-parametric, multi-dimensional, spatial and temporal human behavior or technical observations measured pervasively, and related method for the same are disclosed. An example computer system to process usage data received from a wireless device, the computer system including a memory including machine readable instructions; and a processor to execute the instructions to: process the usage data to identify applications which were sequentially accessed on the wireless device in a time period; build a behavior model based on the identified applications, the behavior model to describe user behavior associated with the wireless device; execute the behavior model to predict usage of an application on the wireless device; based on the prediction, monitor usage of the wireless device to determine an accuracy of the prediction; and update the behavior model based on the accuracy of the prediction.

Abstract: This invention generally discusses wireless devices, servers and communications networks. In particular the invention pertains to performing observations in one or more mobile terminals and processing and distributing the related data in a server side system through layered data processing activities, and conversion of non-parametric data into parameterized form through the utilization of statistical filtering and semantic data structures. It is further explained how such multi-layer, parametrized data can be utilized for predictive purposes, and how feedback loops can be built with the physical world to improve future predictions. The invention is applicable in various applications, for example in systems where precise digital profiles of users need to be built on a continuous basis, and such profiles need to be dynamically linked to one or several actions triggered by emerging characteristics in the data.

Abstract: System for obtaining and analyzing data on online user behavior and other activity having regard to Internet connectable user devices, optionally mobile devices, the system being configured to collect data from a plurality of data sources, wherein the collected data includes at least individual user-level data acquired from user devices and census-level data indicating behavior and demographic characteristics across the entire population of users, active or measured services, with the user-level data being preferably collected using at least one user research panel of controlled constitution, preferably from multiple devices of each participant in the panel, the collected data being indicative of Internet, content, media, application, and/or device usage, organize the obtained user-level and census-level data into a multivalent categorized data set utilizing an ontological metadata schema, determine an electronic deliverable based on an integration of the user-level data and census-level data wherein census-l

Abstract: Electronic system for obtaining data, via one or more digital devices, on user behavior, digital transactions, and exposure relative to digital content and services, or external exposure and associated events between the user and the environment via sensors attached to digital devices, the system being configured to collect data reflecting the content and objects that the user at least potentially perceives as rendered on one or more digital screens attached to smart devices, reconstruct the at least potentially perceived visual landscape based on the collected data, and determine the target and/or level of user attention in view of the reconstruction and associated exposure events detected therein, and to apply locally stored information about rules or fingerprints in the digital object recognition process involving the collected data and validation of the type or identity of user actions, digital content, or external objects, as reflected by the reconstruction recapturing the visual landscape.

Abstract: System and method for behavioral and contextual data analytics are disclosed. An example computer system to process observational data received from a wireless device includes a memory including machine readable instructions and a processor to execute the instructions to: process the observational data to identify temporally adjacent applications to generate usage metric data, the observational data including application usage data; build a behavior model based on the identified temporally adjacent applications, the behavior model to describe user behavior associated with the wireless device; and apply the behavior model to predict a usage duration of a second application in response to usage of a first application.