Mobile Contextual Advertising

....................................................................................................................................3! 1! Introduction .......................................................................................................................3! 1.1! Mobile Marketing.......................................................................................................3! 1.2! Recommender systems..............................................................................................4! 1.3! Research Question......................................................................................................4! 2! Mobile Advertising ...........................................................................................................5! 2.1! Mobile Marketing.......................................................................................................5! 2.2! Spam.............................................................................................................................6! 2.3! Personalisation............................................................................................................6! 2.4! SMS Marketing ...........................................................................................................7! 3! Machine Learning .............................................................................................................8! 3.1! Intelligent Machines ..................................................................................................8! 3.2! Knowledge Based or Machine Learning? ...............................................................9! 3.3! Matching Advertisements with their Context .....................................................10! 3.4! Machine-learning-based Recommendation .........................................................10! 4! Experimental setup .........................................................................................................11! 4.1.1! iThumb................................................................................................................11! 4.2! Pilot experiment .......................................................................................................12! 4.3! Main experiment ......................................................................................................12! 4.4! Data collection ..........................................................................................................13! 4.5! Statistics .....................................................................................................................14! 4.6! Measures....................................................................................................................14! 4.6.1! Precision and Recall ..........................................................................................14! 4.6.2! ROC Curve .........................................................................................................15! 4.7! Machine learning algorithms .................................................................................16! 4.7.1! Rule Induction ...................................................................................................16! 4.7.2! Decision Tree .....................................................................................................17! 4.7.3! K-nearest neighbor algorithm .........................................................................17! 4.7.4! Support Vector Machines.................................................................................17! 4.8! Feature Selection ......................................................................................................18! 4.9! Data coding ...............................................................................................................18! 5! Results...............................................................................................................................18!