Lectures

  • Lecture 1. Introduction

  • Lecture 2. Introduction to Data Mining and Preliminaries

    • Recommended preparation:

      • Completing the Part 2 of your assignment before the lecture

      • Reading Chapter 4 of Sifa's profiling book

      • Reading Section 7.4 of data mining book of Han et. al

    • Slides

  • Lecture 3. Affinity Mining

    • Recommended preparation :

      • Completing Part 1 of your assignment before the lecture

      • Chapter 1 and Sections 5.1 and 5.2.1 of the second edition of the Data Mining book from Han et al.

    • Slides

  • Lecture 4. Latent Pattern Mining I: Introduction

    • Recommended preparation :

      • Chapters 2 and 3 of Matrix and Tensor Factorization for Profiling Player Behavior from Sifa

    • Slides

  • Lecture 5: Latent Pattern Mining II: Algorithms for Unconstrained Factorizations

    • Recommended preparation :

      • Chapter 3 of Matrix and Tensor Factorization for Profiling Player Behavior from Sifa

    • Slides

  • Lecture 6: Latent Pattern Mining III: Recommender Systems

    • Recommended preparation :

      • Chapter 10 of Matrix and Tensor Factorization for Profiling Player Behavior from Sifa

      • Sifa, Rafet, et al. “Matrix and Tensor Factorization Based Game Content Recommender Systems: A Bottom-Up Architecture and a Comparative Online Evaluation.” Fourteenth Artificial Intelligence and Interactive Digital Entertainment Conference. 2018. (Download from https://tinyurl.com/y5tdwlfl)

    • Slides

  • Lecture 7: Latent Pattern Mining IV: Profiling User Behavior with Constrained Models

    • Recommended preparation :

      • Sifa, Rafet, Anders Drachen, and Christian Bauckhage. Profiling in Games: Understanding Behavior from Telemetry. Social Interactions in Virtual Worlds: An Interdisciplinary Perspective (2018). (available under)

      • Chapters 4 and 5 of Matrix and Tensor Factorization for Profiling Player Behavior from Sifa

    • Slides

  • Lecture 8: Latent Pattern Mining V: Factorizing Proximity Data

    • Recommended preparation :

      • Chapter 8 of Matrix and Tensor Factorization for Profiling Player Behavior from Sifa

    • Slides

  • Lecture 9: Introduction to Text Mining

    • Recommended preparation :

      • Chapters 2 and 6 of the Information Retrieval (2009) book of Manning et al.

    • Slides

  • Lectures 10 & 11: Predictive Data Mining for Media Applications

    • Recommended preparation :

      • Chapter 6 in the second edition of Negnevitsky’s book.

      • Rafet Sifa, Anders Drachen, Florian Block, Anisha Dubhashi, Spencer Seongjae Moon, Hao Xiao, Zili Li, Diego Klabjan, Simon Demediuk. “Archetypal Analysis Based Anomaly Detection for Improved Storytelling in Multiplayer Online Battle Arena Games.” In Proceedings of the Australasian Computer Science Week Multiconference, ACM, 2021. URL

    • Slides: