Graduation Semester and Year

2007

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Computer Science

Department

Computer Science and Engineering

First Advisor

Diane Cook

Abstract

Viewers of video now have more choices than ever. As the number of choices increases, the task of searching through these choices to locate video of interest is becoming more difficult. Current methods for learning a viewer's preferences in order to automate the search process rely either on video having content descriptions or on having been rated by other viewers identified as being similar. However, much video exists that does not meet these requirements. To address this need, we use hidden Markov models to learn the preferences of a viewer by combining visual features and closed captions. We validate our approach by testing the learned models on a data set composed of features drawn from movies and user ratings obtained from publicly available data sets.

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

Download

Share

COinS