Publication Type

PhD Dissertation

Publication Date

7-2017

Abstract

That consumers share similar tastes on some products does not guarantee their agreement on other products. Therefore, both similarity and dierence should be taken into account for a more rounded view on consumer preferences. This manuscript focuses on mining this diversity of consumer preferences from two perspectives, namely 1) between consumers and 2) between products. Diversity of preferences between consumers is studied in the context of recommendation systems. In some preference models, measuring similarities in preferences between two consumers plays the key role. These approaches assume two consumers would share certain degree of similarity on any products, ignoring the fact that the similarity may vary across products. We take one step further by measuring different degrees of similarity between two consumers.

Keywords

data mining, database application, recommender systems, collaborative filtering, bundling, profit maximization

Degree Awarded

PhD in Information Systems

Discipline

Categorical Data Analysis | Databases and Information Systems

Supervisor(s)

LAUW, Hady Wirawan

Publication

Singapore Management University

City or Country

Singapore

Copyright Owner and License

Singapore Management University

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Available for download on Friday, October 23, 2020

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