Recommender Systems Notation: Proposed Common Notation for Teaching and Research

02/04/2019
by   Michael D. Ekstrand, et al.
0

As the field of recommender systems has developed, authors have used a myriad of notations for describing the mathematical workings of recommendation algorithms. These notations ap-pear in research papers, books, lecture notes, blog posts, and software documentation. The dis-ciplinary diversity of the field has not contributed to consistency in notation; scholars whose home base is in information retrieval have different habits and expectations than those in ma-chine learning or human-computer interaction. In the course of years of teaching and research on recommender systems, we have seen the val-ue in adopting a consistent notation across our work. This has been particularly highlighted in our development of the Recommender Systems MOOC on Coursera (Konstan et al. 2015), as we need to explain a wide variety of algorithms and our learners are not well-served by changing notation between algorithms. In this paper, we describe the notation we have adopted in our work, along with its justification and some discussion of considered alternatives. We present this in hope that it will be useful to others writing and teaching about recommender systems. This notation has served us well for some time now, in research, online education, and traditional classroom instruction. We feel it is ready for broad use.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/27/2021

Review of Clustering-Based Recommender Systems

Recommender systems are one of the most applied methods in machine learn...
research
03/02/2023

Effective Visualization and Analysis of Recommender Systems

Recommender system exists everywhere in the business world. From Goodrea...
research
04/26/2023

Improvements on Recommender System based on Mathematical Principles

In this article, we will research the Recommender System's implementatio...
research
05/11/2022

Recommending Research Papers to Chemists: A Specialized Interface for Chemical Entity Exploration

Researchers and scientists increasingly rely on specialized information ...
research
05/24/2022

recommenderlab: An R Framework for Developing and Testing Recommendation Algorithms

Algorithms that create recommendations based on observed data have signi...
research
09/12/2019

How robust is MovieLens? A dataset analysis for recommender systems

Research publication requires public datasets. In recommender systems, s...
research
04/18/2023

Report from Dagstuhl Seminar 23031: Frontiers of Information Access Experimentation for Research and Education

This report documents the program and the outcomes of Dagstuhl Seminar 2...

Please sign up or login with your details

Forgot password? Click here to reset