SEMANTIC USER PROFILING FOR DIGITAL ADVERTISING
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | SEMANTIC USER PROFILING FOR DIGITAL ADVERTISING |
| Type de publication | Journal Article |
| Year of Publication | 2015 |
| Auteurs | Hoppe A, Roxin A, Nicolle C |
| Journal | ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH |
| Volume | 49 |
| Pagination | 267-285 |
| Type of Article | Article |
| ISSN | 0424-267X |
| Mots-clés | big data, Data Analysis, Inference, Logical Rules, ontology, Reasoning, semantic web, SWRL, User Profiling |
| Résumé | 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. |