Paper Info
Title
Semantic tags generation and retrieval for online advertising
Abstract
One of the main problems in online advertising is to display ads which are relevant and appropriate w.r.t. 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.
Year
DOI
Venue
2010
10.1145/1871437.1871576
CIKM
Keywords
DocType
Citations 
semantic tags generation,online advertising,efficient ads campaign,real user,ads content,hybrid ranking system,ads provider,classical search engine result,social tagging system,search engine,ranking system,dbpedia dataset
Conference
9
PageRank 
References 
Authors
0.69
14
4
Name
Order
Citations
PageRank
Roberto Mirizzi133016.59
Azzurra Ragone251140.86
Tommaso Di Noia31857152.07
Eugenio Di Sciascio41733147.71