Hours:
4 hours (1 credit)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

The course deals with the application of machine learning methods to Web data, in particular in the context of two research problems: detecting Web bots and predicting purchases in online stores. The first problem is due to the presence of artificial agents on the Web which pose a threat to the website security, privacy, and performance. Continuous development of artificial agents’ technology makes detection of Web bot, both in the offline and real-time settings, harder and harder. The second problem is connected with discovering various user profiles on e-commerce websites and identifying user sessions with high probability of making a purchase. The problems under consideration are key issues in the era of the rapid development of e-commerce, advanced Web-based technologies, and big data.

Course Contents in brief:

1. Introduction to Web usage mining (1 hour)
   Web usage data. Web usage mining in the context of online stores.
   Data pre-processing for Web usage mining. Reconstruction of user sessions.
2. Web bot detection (2 hours)
   Problems of offline and online bot detection. Characteristics and differences in bot and human Web traffic. Feature selection and feature extraction for bot detection. Offline bot detection with supervised and unsupervised learning methods. Online bot detection.
3. Online purchase prediction (1 hour)
   Problem of predicting online purchases. Feature selection for online purchase prediction.
   Purchase prediction with machine learning methods.

Schedule:

• Day 1 - 21/05/2024, 9:00-13:00