Using visual and text features for direct marketing on multimedia messaging services domain |
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Authors: | Sebastiano Battiato Giovanni Maria Farinella Giovanni Giuffrida Catarina Sismeiro Giuseppe Tribulato |
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Affiliation: | (1) Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, Catania, 95125, Italy;(2) Imperial College Business School, Imperial College London, South Kensington, Campus, London, SW7 2AZ, UK |
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Abstract: | Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience.
Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect
to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing
process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in
particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate
that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes
a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features
to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS)
show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed
approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.
Sebastiano Battiato
was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in
Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics
in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania.
His research interests include image enhancement and processing, image coding and camera imaging technology. He published
more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international
patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference
committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE
Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International
Computer Vision Summer School). He is a Senior Member of the IEEE.
Giovanni Maria Farinella
is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research
group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006.
His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received
his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from
the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings.
He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International
Summer School on Computer Vision (ICVSS).
Giovanni Giuffrida
is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of
Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992,
and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience
in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations.
His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published
several papers on data mining and its applications. He is a member of ACM and IEEE.
Catarina Sismeiro
is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from
the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before
joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern
California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive
environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the
use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared
in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007
Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST
award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing.
Giuseppe Tribulato
was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in
Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining
techniques, recommendation systems and customer targeting.
![MediaObjects/11042_2008_250_Fige_HTML.gif](/content/x6pn26144837w21n/MediaObjects/11042_2008_250_Fige_HTML.gif) |
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Keywords: | Visual and text features Learning in time and space constrained domains Multimedia messaging services Direct marketing |
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