Search results for "User profile"
showing 6 items of 26 documents
Ontology-based Integration of Web Navigation for Dynamic User Profiling
2015
The development of technology for handling information on a Big Data-scale is a buzzing topic of current research. Indeed, improved techniques for knowledge discovery are crucial for scientific and economic exploitation of large-scale raw data. In research collaboration with an industrial actor, we explore the applicability of ontology-based knowledge extraction and representation for today's biggest source of large-scale data, the Web. The goal is to develop a profiling application, based on the implicit information that every user leaves while navigating the online, with the goal to identify and model preferences and interests in a detailed user profile. This includes the identification o…
Dynamic, Behavior-Based User Profiling Using Semantic Web Technologies in a Big Data Context
2013
pp. 363-372; International audience; The success of shaping the e-society is crucially dependent on how well technology adapts to the needs of each single user. A thorough understanding of one's personality, interests, and social connections facilitate the integration of ICT solutions into one's everyday life. The MindMinings project aims to build an advanced user profile, based on the automatic processing of a user's navigation traces on the Web. Given the various needs underpinned by our goal (e.g. integration of heterogeneous sources and automatic content extraction), we have selected Semantic Web technologies for their capacity to deliver machine-processable information. Indeed, we have…
GUI personalization framework driven by personal semantic user profile
2017
Sovelluskehys käyttöliittymän personointiin käyttäen semanttista käyttäjäprofiilia. Internetin kehittyessä maailma verkostoituu yhä enemmän. Käytämme päivittäin monia laitteita ja erilaisia käyttöliittymiä, mutta vaikka ne monesti jakavat yleisiä käytänteitä ja kuvakkeita, eivät ne kuitenkaan mukaudu yksittäisen käyttäjän tarpeisiin. Vaikka ihmisillä on monia eri ominaisuuksia tai rajoitteita, jotka vaikeuttavat käyttöliittymän omaksumista, palvelun tai ohjelman näkökulmasta käyttäjät mielletään silti yhtenä homogeenisenä joukkona, jonka on mukauduttava käyttöliittymään. Omaksumiskykyyn vaikuttavia tekijöitä ovat esimerkiksi kieli, ikä, koulutustausta ja kulttuuri. Mukautuvan käyttöliittymä…
Customer Feedback System : Evolution Towards Semantically-enchanced Systems
2015
The digital economy requires services be created in nearly real time – while continuously listening to the customer. Managing and analysing the data collected about products and customers become very critical. Successful companies must collect data regarding customer behaviour in a sensible manner, understand their customers and engage in constant interaction with them. Nowadays, having a huge data storage capacity, everyone collects data and hopes that it will be useful someday. But, it is frustrating when you do not know whether something useful will come out of it. It is not a problem to collect data, but it is very difficult to analyse it. To utilize the data they collect and analyse cu…
A two-step, user-centered approach to personalized tourist recommendations
2017
Geo-localized, mobile applications can simplify a tourist visit, making the relevant Point of Interests more easily and promptly discernible to users. At the same time, such solutions must avoid creating unfitting or rigid user profiles that impoverish the users' options instead of refining them. Currently, user profiles in recommender systems rely on dimensions whose relevance to the user is more often presumed than empirically defined. To avoid this drawback, we build our recommendation system in a two-step process, where profile parameters are evaluated preliminarily and separately from the recommendations themselves. We describe this two-step evaluation process including an initial surv…
Application of the Information Bottleneck method to discover user profiles in a Web store
2018
The paper deals with the problem of discovering groups of Web users with similar behavioral patterns on an e-commerce site. We introduce a novel approach to the unsupervised classification of user sessions, based on session attributes related to the user click-stream behavior, to gain insight into characteristics of various user profiles. The approach uses the agglomerative Information Bottleneck (IB) algorithm. Based on log data for a real online store, efficiency of the approach in terms of its ability to differentiate between buying and non-buying sessions was validated, indicating some possible practical applications of the our method. Experiments performed for a number of session sampl…