COURSE ANNOUNCEMENT

Web usage mining on e-commerce websites

Grażyna Suchacka – University of Opole


Duration:  8 hours
When: 14 – 16 June, 2021 
Where: Microsoft Teams
PhD credits (DIBRIS metric): 2

PLEASE ENROL HERE (attendance is FREE):
https://docs.google.com/forms/d/e/1FAIpQLSf8jfnT-ITB9ujI8OY2AOPJeoRBkUb7X4O3T9HQVDLe0S9LNQ/viewform?usp=sf_link


Abstract
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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 Web bot 
detection, 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.


Program
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(Italian times, CEST)

MONDAY, 14 JUNE 2021 h 14.00 - 16.00 
Lecture 1 "Introduction to Web usage mining"
-	Web usage data
-	Web usage mining in the context of online stores
-	Characteristics and differences in bot and human Web traffic
-	Data pre-processing for Web usage mining, reconstruction of user sessions

TUESDAY, 15 JUNE 2021 h 11.00 - 13.00 
Lecture 2 "Web bot detection, part 1"
-	Problems of offline and online bot detection
-	Feature selection and feature extraction for bot detection
-	Offline bot detection with supervised classification methods

TUESDAY, 15 JUNE 2021 h 14.00 - 16.00 
Lecture 3 "Web bot detection, part 2"
-	Offline bot detection with unsupervised classification methods
-	Online bot detection

WEDNESDAY, 16 JUNE 2021 h 11.00 - 13.00 
Lecture 4 "Online purchase prediction"
-	Problem of predicting online purchases
-	Feature selection for online purchase prediction
-	Purchase prediction with machine learning methods