Personalization and Recommender Systems

ITIS 6410/8410

Spring 2008

http://www.sis.uncc.edu/~davils/itis6410/itis6410.html


Course Description

This course is an introduction to the application of personalization and recommender systems techniques in information systems. Topics include: historical, individual and commercial perspectives; underlying approaches to content-based and collaborative recommendation; techniques for building user models; acceptance issues; and case-studies drawn from research prototypes and commercially deployed systems.

Meeting

6:30-9:15pm, Thursday, Woodward 120

The course session will typically (not necessarily always) be split into three segments, with short breaks in between: 6:30-7:20, 7:30-8:20, and 8:30-9:15.

Textbook

No textbook. Readings will be provided.

Instructor

Readings and Homework

WeekDateNotesReadingAssignment
1 Jan 10 Course Introduction

Topics

Academic Integrity

Students are responsible for knowing and observing the requirements of The UNC Charlotte Code of Student Academic Integrity (Policy Statement #105). The code forbids cheating, fabrication, or falsification of information, multiple submission of academic work, plagiarism, abuse of academic materials, and complicity in academic dishonesty. There are no special requirements regarding academic integrity in this course. The code will be strictly enforced and is binding on the students. Grade and academic evaluations in this course include a judgment that the student's work is free from academic dishonesty of any type; and grades in this course therefore should be and will be adversely affected by academic dishonesty. Students who violate the code can be expelled from UNC Charlotte. The normal penalty for a first offense is zero credit on the work involving dishonesty and further substantial reduction of the course grade. In almost all cases the course grade is reduced to an F. Copies of the Code can be obtained from the Dean of Students Office or me. Standards of academic integrity will be enforced in this course. Students are expected to report cases of academic dishonesty immediately.