Troubles in Deciding? How Recommender Technology Can Help Consumers ChooseSpeaker: Pearl Pu – Preverenges, Switzerland
Topic(s): Web, Mobile and Multimedia Technologies
As online stores offer practically an infinite shelf space, recommender systems are playing an increasingly important role in helping users search and discover items that they truly want. But are they also helping them make better decisions?
In decision theory, a choice problem is defined as the task of choosing an option out of a set of alternatives. The larger the alternative set is, and the more features definine each option, the more difficult it is for users to choose. I will give an overview of recent literature in decision theory that explains the discrepancies between normative models of how people should reason and empirical studies of how they in fact think and decide. This discrepancy points out that we have trouble deciding in ubiquitous situations such as finding something to buy in online stores. I will explain what regulates this difficulty such as decision accuracy vs. user effort.
I then describe a special type of recommender technology, critiquing based recommender systems, designed specifically to help users make better decisions while minimizing their cognitive effort. I will describe methods to compute critiques as well as how to present them to users. I illustrate the techniques with examples from actual implementations and user studies.
About this LectureNumber of Slides: 50
Duration: 40 minutes
Languages Available: English
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