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Recommender Systems Notation: Proposed Common Notation for Teaching and Research
arXiv.org
04 Feb 2019
Abstract
Boise State University Computer Science Faculty Publications and
Presentations 177 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.
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Details
- Title
- Recommender Systems Notation: Proposed Common Notation for Teaching and Research
- Creators
- Michael D EkstrandJoseph A Konstan
- Publication Details
- arXiv.org
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Information Science
- Other Identifier
- 991021868095104721