2014 ImprovingSalesDiversitybyRecomm

• (Vargas & Castells, 2014) ⇒ Saúl Vargas, and Pablo Castells. (2014). “Improving Sales Diversity by Recommending Users to Items.” In: Proceedings of the 8th ACM Conference on Recommender systems. ISBN:978-1-4503-2668-1 doi:10.1145/2645710.2645744

Subject Headings:

Notes

• It proposes a reversed-neighborhood Collaborative Filtering algorithm, which exchanges the roles of users and items, and then computes the recommendation scores of all the user-item pairs following the original procedure.
• Its experiments suggest that the method achieve better recommendation coverage and recommendation diversity (at the expense of prediction quality).

Cited By

• http://scholar.google.com/scholar?q=%222014%22+Improving+Sales+Diversity+by+Recommending+Users+to+Items
• http://dl.acm.org/citation.cfm?id=2645710.2645744&preflayout=flat#citedby

Quotes

Abstract

Sales diversity is considered a key feature of Recommender Systems from a business perspective. Sales diversity is also linked with the long-tail novelty of recommendations, a quality dimension from the user perspective. We explore the inversion of the recommendation task as a means to enhance sales diversity - and indirectly novelty - by selecting which users an item should be recommended to instead of the other way around. We address the inverted task by two approaches: a) inverting the rating matrix, and b) defining a probabilistic reformulation which isolates the popularity component of arbitrary recommendation algorithms. We find that the first approach gives rise to interesting reformulations of nearest-neighbor algorithms, which essentially introduce a new neighbor selection policy. The second approach, as well as the first, ultimately result in substantial sales diversity enhancements, and improved trade-offs with recommendation precision and novelty. Two experiments on movie and music recommendation datasets show the effectiveness of the resulting approach, even when compared to direct optimization approaches of the target metrics proposed in prior work.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 ImprovingSalesDiversitybyRecomm	Saúl Vargas Pablo Castells			Improving Sales Diversity by Recommending Users to Items				10.1145/2645710.2645744		2014