Semantic tags generation and retrieval for online advertising

Technical Report , Politecnico di Bari - 2010
One of the main problem in online advertising is to display ads which are relevant and appropriate \wrt what the user is looking for. Often search engines fail to reach this goal as they do not consider semantics attached to keywords. In this paper we propose a system that tackles the problem by two different angles: help (i) advertisers to create more efficient ads campaigns and (ii) ads providers to properly match ads content to keywords in search engines. We exploit semantic relations stored in the DBpedia dataset and use an hybrid ranking system to rank keywords and to expand queries formulated by the user. Inputs of our ranking system are (i) the DBpedia dataset; (ii) external information sources such as classical search engine results and social tagging systems. We compare our approach with other RDF similarity measures, proving the validity of our algorithm with an extensive evaluation involving real users.

BibTex references

author = {Roberto Mirizzi and Azzurra Ragone and Tommaso {Di Noia} and Eugenio {Di Sciascio}},
title = "Semantic tags generation and retrieval for online
institution = "Politecnico di Bari",
year = "2010",
url = "

Other publications in the database

SisInf Lab - Information Systems Laboratory

Research group of Politecnico di Bari
Edoardo Orabona St, 4 Bari, Italy