Date of Award

12-31-2018

Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor

Dan Simovici

Second Advisor

Alfred Noel

Third Advisor

Wei Ding

Abstract

We apply polarities, axiallities and the notion of entropy to the task of identifying marketable items and the customers that should be approached in a marketing campaign. An algorithm that computes the criteria for identifying marketable items and the corresponding experimental work is also included.

The dynamics of players rankings play an important role in team sports. We use Kendall’s tau and Spearman’s rho distances between rankings to study player scoring ranking dynamics in the NBA over the full 2014 regular season. For each team, we study the distances between sequential games, noting the differences between the two distances. Additionally, we define the consistency of teams based on their ranking dynamics. Team consistency and winning percentage are compared. Finally, we use our findings to produce actionable results for sports managers.

Commercial Real Estate development constitutes an important part of the US economy. A small but very valuable percentage of proposed projects, however, are abandoned. Estimating the probability of project completion has significant economic value. In this paper. we generalize an information theory based measure of confidence for the recommendations created by collaborative filtering algorithms. Due to the imbalanced nature of the data, we utilize boosting techniques to improve our prediction. Finally, we used our approach to predict the completion rate of $2.2 trillion worth of commercial real estate projects supporting each result with our new confidence measure.

Comments

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