This thesis was submitted by Dr. Dominik Kowald to the Institute of Interactive Systems and Data Science of Graz University of Technology in Austria on the 5th of September 2017 for the attainment of the degree 'Dr.techn'. The supervisors of this thesis have been Prof. Stefanie Lindstaedt and Ass.Prof. Elisabeth Lex from Graz University of Technology, and the external assessor has been Prof. Tobias Ley from Tallinn University. In the current enthusiasm around Data Science and Big Data Analytics, it is important to mention that only theory-guided approaches will truly enable us to fully understand why an algorithm works and how specific results can be explained. It was the goal of this dissertation research to follow this path by demonstrating that a recommender system inspired by human memory theory can have a true impact in the field.
翻译:该论文由Dominik Kowald博士于2017年9月5日向奥地利格拉茨技术大学互动系统和数据科学研究所提交,以获得“Dr.techn”学位。该论文的主管是格拉茨技术大学的Stefanie Lindstaedt和As.Prof. Elisabeth Lex教授,外部评估员是塔林大学的Tobias Ley教授。在目前围绕数据科学和大数据分析学的热情下,必须指出,只有理论引导的方法才能真正使我们充分理解算法工作的原因和如何解释具体结果。这一论文研究的目的是通过证明受人类记忆理论启发的推荐系统能够在实地产生真正的影响,从而沿着这条道路走下去。