Name
Title | ||
|---|---|---|
Customer recommendation based on profile matching and customized campaigns in on-line social networks. |
Abstract | ||
|---|---|---|
We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-Line Social Network profiles. In particular, we associate suitable categories and subcategories to both user and brand profiles in the considered On-line Social Network. When categories involve posts and comments, the comparison is based on word embedding, and this allows to take into account the similarity between the topics of particular interest for a brand and the user preferences. Furthermore, user personal information, such as age, job or genre, are used for targeting specific advertising campaigns. Results on real Facebook dataset show that the proposed approach is successful in identifying the most suitable set of users to be used as target for a given advertisement campaign.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341161.3345621 | ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining
Vancouver
British Columbia
Canada
August, 2019 |
Keywords | Field | DocType |
social advertising, recommendation system, profile matching, semantic similarity | World Wide Web,Social network,Computer science,Artificial intelligence,Machine learning | Conference |
ISSN | ISBN | Citations |
2473-9928 | 978-1-4503-6868-1 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mariella Bonomo | 1 | 0 | 0.34 |
| Gaspare Ciaccio | 2 | 0 | 0.34 |
| Andrea De Salve | 3 | 55 | 10.95 |
| Simona E. Rombo | 4 | 192 | 22.21 |