Adaptive music recommendation system
Name
703439198-MIT.pdf
Description
Full printable version
Size
3.68 MB
Format
Adobe PDF
Checksum (MD5)
c4c1a27212a0ea85742f7492212770b8
Author(s)
Yang, Fan, M. Eng. Massachusetts Institute of Technology
Advisor(s)
Steve Ward.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
While sources of digital music are getting more abundant and music players are becoming increasingly feature-rich, we still struggle to find new music that we may like. This thesis explores the design and implementation of the MusicPlanner - a music recommendation application that utilizes a goal-oriented framework to recommend and play music. Goal-oriented programming approaches problems by modeling them using Goals, Techniques, and a Planner. The Goals are representations of a user's intent, while the Techniques are the methods that can be used to satisfy the Goals. The Planner connects the Goals and Techniques in a user-defined way to find solutions to user's requests. In the MusicPlanner, the Planner defines the top level Goal of recommending music, which can be satisfied by a set of recommendation Techniques. Each of the recommendation Techniques then declares the sub-Goal of playing music, which can be satisfied by a set of play Techniques. The Planner evaluates each of the Techniques and iterates through the results to choose the best set of Techniques to satisfy the top-level goal of music recommendation. The MusicPlanner allows the user to create personal music stations and for each station, constructs a model of user's music taste based on queries and feedback to the songs played. The extensible design of the architecture and the ease of implementing the MusicPlanner show how goal-oriented framework can simplify the work for programmers. In evaluating the performance of the MusicPlanner, we demonstrate that the Planner in the goal-oriented framework outperforms each individual recommendation Technique.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 61-63).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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