Abstract: Method and system for advertisement retargeting using predictive user intent patterns. A survey server collects behavioral data from a plurality of user devices visiting a website. The survey server collects survey participation data related to the visit of the website from some of the plurality of user devices, and determines an intent of corresponding users based on the survey participation data. The survey server analyzes the intent of the users and the related behavioral data to generate predictive user intent patterns. The survey server collects current behavioral data from a current user device visiting a current website. The survey server determines an intent of the user of the current user device while visiting the current website, based on the current behavioral data and the predictive user intent patterns. An advertisement server selects a retargeting advertisement directed to the current website for the current user device using the determined intent.

Abstract: A method and survey server for performing a web survey based on behavioral data specific to a web page. Behavioral data related to a specific web page of a website are collected from a plurality of user devices. The behavioral data are representative of a series of actions performed by a user of each of the plurality of user devices while visiting the specific web page. A processing unit of the survey server compares the behavioral data collected from the plurality of user devices with reference behavioral data. The processing unit further determines whether to invite or not the user of a particular user device among the plurality of user devices to participate to a web survey related to the specific web page, based on a result of the comparison.

Abstract: The present disclosure relates to a method and survey server for generating predictive patterns for website analysis. Behavioral data are collected at the survey server from a plurality of user devices. The behavioral data are representative of actions performed by a user of each of the plurality of user devices while visiting a website. Server survey participation data are also collected at the survey server from some of the plurality of user devices. The survey participation data correspond to survey information received from the users of each of the plurality of the user devices when visiting the website. The survey participation data and related behavioral data are analyzed by the survey server to generate predictive survey participation patterns. Contextual data may also collected from some of the plurality of user devices and analyzed with related collected contextual data for generating predictive contextual patterns.

Abstract: A method and survey server for generating performance metrics of URLs of a website. The survey server collects website visit data from a plurality of user devices. The website visit data comprise URLs of webpages of the website displayed on each specific user device during a visiting of the website by a user of the specific user device. The survey server also collects participation data from some of the plurality of user devices. The survey participation data correspond to survey information received from the users of the user devices in relation to the visit of the website, and comprise an indication of the users having either or not fulfilled a purpose of visit. The survey server further analyzes the website visit data and the survey participation data to generate performance metrics of the URLs of the website with respect to fulfilling the purpose of visit of the website.

Abstract: The present method and system provide personalized web content to user devices under control of a user. In one alternative, the method comprises receiving a request to visit a website from a remote computer hosting a web browser; exchanging data with the remote computer to obtain a recognisable identifier from the remote computer; after reception of the recognisable identifier, retrieving from a personalization database a personalization parameter associated with said identifier; generating, according to a database of web contents and the personalization parameter, a personalized website visit content comprising one of: 1) a different HTML document, 2) a different Cascading Style Sheet (CSS), and 3) a different web content to be provided according to the HTML document, than a non-personalized webpage; and transmitting the personalized website visit content to the remote computer.

Abstract: The present relates to a method and system for operating a virtual energy network. The method and system receives electricity at a local energy network from an electric grid, stores at an energy storage appliance electricity received from the electric grid at a first period of time, and provides electricity from the energy storage appliance to the local energy network at a second period of time. The cost of the electricity provided by the electric grid is lower at the first period of time than at the second period of time. The energy storage appliance is connected to a management unit via a communication network, from which it receives an energy storage policy. Also, the electric grid, a plurality of energy storage appliances connected to the electric grid and to a corresponding plurality of local energy networks, and the management unit constitute a virtual energy network.

Abstract: The present relates to a method and a system for generating a mobile device network footprint index. The method and system receives, at an analytic system, information related to a network footprint of mobile devices. This information consists in records representative of mobile IP sessions occurring on a mobile IP network. Then, the method and system aggregates, by means of the analytic system, the information by models of mobile devices; and processes, by means of the analytic system, the aggregated information to calculate at least one metric representative of a network footprint of a selected model of mobile device over a selected period of time. A mobile device network footprint index is generated, by means of the analytic system, by calculating the at least one metric for several selected models of mobile devices over the selected period of time.

Abstract: A method and system for collecting and analyzing IPTV traffic in an IPTV network including end user premises, an access network, and an IP core network, wherein filtering sub-systems are deployed to collect in real time IPTV traffic using at least one access technology. The filtering sub-systems are deployed in at least one location selected from the group consisting of the end user premises, the access network, and the IP core network, and the at least one location of the filtering sub-systems is selected to collect IPTV traffic with a granularity at the level of the end users. The collected IPTV traffic is transmitted from the filtering sub-systems to a centralized analytic system, the collected IPTV traffic is aggretated in relation to the end users, and business intelligence and marketing oriented analysis is performed over the collected IPTV traffic using the centralized analytic system.

Abstract: A method for extracting data information from data traffic flowing through a mobile IP network, in view of providing a substantially real-time view of the mobile IP network comprises receiving a copy of the data traffic and extracting sequentially, in relation to a layered-structure of the data traffic, information contained in the received copy of the data traffic. A system to carry out such method comprises a receiver of a copy of the data traffic and an extractor for sequentially extracting, in relation to a layered-structure of the data traffic, information contained in the received copy of the data traffic.