Search results for "User Profiling"

Automatic User Profile Mapping To Marketing Segments In A Big Data Context

2015

International audience; Within the discussion about the analysis methods for Big Data contexts, semantic technologies often get discarded for reasons of efficiency. While machine learning and statistics are known to have shortcomings when handling natural language, their advantages in terms of performance outweigh potential concerns. We argue that even when handling vast amounts of data, the usage of semantic technologies can be profitable and demonstrate this by developing an ontology-based system for automatically mapping user profiles to pre-defined marketing segments.

Multi-party metering: An architecture for privacy-preserving profiling schemes

2013

Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing …

User Activity Recognition for Energy Saving in Smart Homes

2015

Abstract Energy demand in typical home environments accounts for a significant fraction of the overall consumption in industrialized countries. In such context, the heterogeneity of the involved devices, and the non negligible influence of the human factor make the optimization of energy use a challenging task; effective automated approaches must take into account basic information about users, such as the prediction of their course of actions. Our proposal consists in learning customized structural models for common user activities for predicting the trend of energy consumption; the approach aims to lower energy demand in the proximity of predicted peak loads so as to keep the overall cons…

User detection through multi-sensor fusion in an AmI scenario

2012

Recent advances in technology, with regard to sensing and transmission devices, have made it possible to obtain continuous and precise monitoring of a wide range of qualitatively diverse environments. This has boosted the research on the novel field of Ambient Intelligence, which aims at exploiting the information about the environment state in order to adapt it to the user’s preference. In this paper, we analyze the issue of detecting the user’s presence in a given region of the monitored area, which is crucial in order to trigger subsequent actions. In particular, we present a comprehensive framework that turns data perceived by sensors of different nature, and with possible imprecision, …

Discovering Homophily in Online Social Networks

2018

During the last ten years, Online Social Networks (OSNs) have increased their popularity by becoming part of the real life of users. Despite their tremendous widespread, OSNs have introduced several privacy issues as a consequence of the nature of the information involved in these services. Indeed, the huge amount of private information produced by users of current OSNs expose the users to a number of risks. The analysis of the users’ similarity in OSNs is attracting the attention of researchers because of its implications on privacy and social marketing. In particular, the homophily between users could be used to reveal important characteristics that users would like to keep hidden, hence …

DYNAMIC SEMANTIC USER PROFILING FROM IMPLICIT WEB NAVIGATION DATA

2014

International audience; On the Web, pages are often dynamically generated and allow publishers to individually adapt contents to each viewer. Underlying systems must correctly understand the user's context - crucial especially in the case of online advertisement placement. The article at hand describes our proposition of a novel profiling system, adapted to the special needs of digital advertising. Based on Semantic Web Technologies, the MindMinings system relies on an ontology to enable thorough understanding of each user's context and needs. The underlying ontology structure also provides enhanced interoperability with semantically annotated knowledge resources, notably vocabularies from …

Semantic User Profiling for Digital Advertising

2015

International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.

User Activity Recognition via Kinect in an Ambient Intelligence Scenario

2014

The availability of an ever-increasing kind of cheap, unobtrusive, sensing devices has stressed the need for new approaches to merge raw measurements in order to realize what is happening in the monitored environment. Ambient Intelligence (AmI) techniques exploit information about the environment state to adapt the environment itself to the users’ preferences. Even if traditional sensors allow a rough understanding of the users’ preferences, ad-hoc sensors are required to obtain a deeper comprehension of users’ habits and activities. In this paper we propose a framework to recognize users’ activities via a depth and RGB camera device, namely the Microsoft Kinect. The proposed approach takes…

Gait Analysis Using Multiple Kinect Sensors

2014

A gait analysis technique to model user presences in an office scenario is presented in this chapter. In contrast with other approaches, we use unobtrusive sensors, i.e., an array of Kinect devices, to detect some features of interest. In particular, the position and the spatio-temporal evolution of some skeletal joints are used to define a set of gait features, which can be either static (e.g., person height) or dynamic (e.g., gait cycle duration). Data captured by multiple Kinects is merged to detect dynamic features in a longer walk sequence. The approach proposed here was been evaluated by using three classifiers (SVM, KNN, Naive Bayes) on different feature subsets.

Pricavy-Preserving Aspects for Data Mining in ICT Services

The steady adoption of systems for profiling users behavior, collecting and critically interpreting as much information as possible about likes and dislikes, interests and habits of Internet residents and generic services consumers have rapidly become some of the hottest keywords within networking research community. Indeed, mining information about users behavior is an advantage for both service providers and service customers: on one side, providers can improve their revenues by focusing on the most successful features of their services, while on the other side, users can enjoy services which reflect closer their specific needs. There are many examples of user profiling applications. Inte…