• Chain-based recommendations 

  Rana, Arpit (2019-10-14)

  Recommender systems are discovery tools. Typically, they infer a user's preferences from her behaviour and make personalized suggestions. They are one response to the overwhelming choices that the Web affords its users. ...
• Subprofile aware diversification of recommendations 

  Kaya, Mesut (University College Cork, 2019)

  A user of a recommender system is more likely to be satisfied by one or more of the recommendations if each individual recommendation is relevant to her but additionally if the set of recommendations is diverse. The most ...
• An approach to robustness in stable marriage and stable roommates problems 

  Genc, Begum (University College Cork, 2019)

  This dissertation focuses on a novel concept of robustness within the context of matching problems. Our robustness notion for the stable matching framework is motivated by the unforeseen events that may occur after a ...
• Rich-context: an unsupervised context-driven recommender system based on user reviews 

  Peña, Francisco J. (University College Cork, 2019)

  In the digital era, users have, more than at any point in history, a large amount of products or services to choose from. Recommender systems help to overcome this problem by suggesting which products or services to consume ...
• Preference inference based on lexicographic and Pareto models 

  George, Anne-Marie (University College Cork, 2019)

  Preferences play a crucial part in decision making. When supporting a user in making a decision, it is important to analyse the user’s preference information to compute good recommendations or solutions. However, often it ...

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