An Analysis Of Recommendation Algorithms

3557 Words Nov 11th, 2014 15 Pages
An Analysis of Recommendation Algorithms
(Status Report)

K. Suzanne Carroll
School of Information
University of Texas
Austin, TX 78701
U.S.A.
ksuzannecarroll@utexas.edu Ankita De
Department of Computer Science
University of Texas
Austin, TX 78701
U.S.A.
ankitade@cs.utexas.edu

1. INTRODUCTION
Recently recommendation system use has risen in popularity as their algorithms interpret user preferences and guide customers to movies to watch, books to purchase, or restaurants to dine. This popularity, along with competitions where students build novel recommendation systems, peaked our interest in the mechanics behind recommendation algorithms. We have design our project to explore and evaluate the algorithms which influence how recommendation systems operate.
Following the submission of our project proposal a month ago, our project has changed course. Given our team 's relative inexperience in the field of recommendation systems, we are now interested in conducting an analysis to fully understand how the various recommendation methods and techniques perform with mutliple datasets.
This status report will explain the new methods we intend to evaluate and introduce our chosen datasets. We will explain and summarize this new project within the Summary section, go into detail on the exact data, tools, and methods we will use in the Methods section, and provde a progress update in all of the remaining sections.

2. SUMMARY
Our project came about because we are both interested…
Open Document