Title :
Targeted advertising in the online video space
Author :
Prasad, Sharanjai ; Lutes, Andrew ; Jenvey, Eric ; Sutton, William ; Stephenson, Amanda ; MacDowell, Courtney ; Barker, Jennifer ; Scherer, William T.
Author_Institution :
Dept. of Syst. & Inf. Eng., Univ. of Virginia, Charlottesville, VA, USA
Abstract :
Videology is an online video advertising, optimization, and yield management solutions provider whose business strategy is to purchase online video advertising inventory from content providers and deliver ads to their clients using behavioral and demographic targeting to maximize value. The Capstone team used a diverse set of analytical tools, including Time Series models, Principal Component analysis, Decision Tree Optimization, Generalized Linear Models, K-Means clustering, and linear programming to improve efficiency in the online video advertisement space by connecting consumers with advertisements on which they are most likely to click. Trends, patterns, and anomalies in the data may lead to new targeting opportunities for Videology.
Keywords :
advertising data processing; decision trees; learning (artificial intelligence); linear programming; pattern clustering; principal component analysis; time series; Capstone team; K-means clustering; behavioral targeting; business strategy; content provider; data anomaly; data pattern; data trend; decision tree optimization; demographic targeting; generalized linear model; linear programming; online video advertisement space; online video advertising; online video space; principal component analysis; targeted advertising; time series model; videology; yield management solutions provider; Advertising; Clustering algorithms; Decision trees; Educational institutions; Prediction algorithms; Training; Videos;
Conference_Titel :
Systems and Information Design Symposium (SIEDS), 2012 IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
978-1-4673-1285-1
DOI :
10.1109/SIEDS.2012.6215146
