Name
Abstract | ||
|---|---|---|
This paper focuses on Contextual Advertising, which is devoted to display commercial ads within the content of third-party Web pages. In the literature, several approaches estimate the relevance of an ad based only on syntactic approaches. However, these approaches may lead to the choice of a remarkable number of irrelevant ads. In order to solve these drawbacks, solutions that combine a semantic phase with a syntactic phase have been proposed. Framed within this approach, we propose an approach that uses to a semantic network able to supply commonsense knowledge. To this end, we developed and implemented a system that uses the ConceptNet 3 database. To our best knowledge this is the first attempt to use information provided by ConceptNet in the field of Contextual Advertising. Several experiments have been performed aimed at comparing the proposed system with a state-of-the-art system. Preliminary results show that the proposed system performs better. |
Year | Venue | Keywords |
|---|---|---|
2011 | KDIR 2011: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND INFORMATION RETRIEVAL | Contextual advertising,Recommender systems,Information filtering |
Field | DocType | Citations |
Contextual advertising,World Wide Web,Computer science,Artificial intelligence,Machine learning | Conference | 6 |
PageRank | References | Authors |
0.44 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giuliano Armano | 1 | 325 | 42.89 |
| Alessandro Giuliani | 2 | 170 | 25.21 |
| eloisa vargiu | 3 | 227 | 32.75 |