SEMANTIC USER PROFILING FOR DIGITAL ADVERTISING

被引：0

作者：

Hoppe, Anett ^{[1
]}

Roxin, Ana ^{[1
]}

Nicolle, Christophe ^{[1
]}

机构：

[1] Univ Bourgogne, Fac Sci Mirande, Checksem Res Grp, Aile Sci Ingenieur LE21, F-21078 Dijon, France

来源：

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH | 2015年 / 49卷 / 03期

关键词：

Ontology; Semantic Web; Reasoning; Logical Rules; SWRL; Inference; Big Data; User Profiling; Data Analysis; WEB;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：267 / 285

页数：19

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