2011 ClickShapingtoOptimizeMultipleO

• (Agarwal et al., 2011) ⇒ Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, and Xuanhui Wang. (2011). “Click Shaping to Optimize Multiple Objectives.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011) Journal. ISBN:978-1-4503-0813-7 doi:10.1145/2020408.2020435

Subject Headings: Multi-Objective Recommendation, Multi-Objective Optimization.

Cited By

• http://scholar.google.com/scholar?q=%222011%22+Click+Shaping+to+Optimize+Multiple+Objectives
• http://dl.acm.org/citation.cfm?id=2020408.2020435&preflayout=flat#citedby

2012

• (Rodriguez et al., 2012) ⇒ Mario Rodriguez, Christian Posse, and Ethan Zhang. (2012). “Multiple Objective Optimization in Recommender Systems.” In: Proceedings of the sixth ACM conference on Recommender systems.

Quotes

Author Keywords

• Algorithms; click shaping; constrained optimization; design; multi-objective; on-line information services

Abstract

Recommending interesting content to engage users is important for web portals (e.g. AOL, MSN, Yahoo !, and many others). Existing approaches typically recommend articles to optimize for a single objective, i.e., number of clicks. However a click is only the starting point of a user's journey and subsequent downstream utilities such as time-spent and revenue are important. In this paper, we call the problem of recommending links to jointly optimize for clicks and post-click downstream utilities click shaping. We propose a multi-objective programming approach in which multiple objectives are modeled in a constrained optimization framework. Such a formulation can naturally incorporate various application-driven requirements. We study several variants that model different requirements as constraints and discuss some of the subtleties involved. We conduct our experiments on a large dataset from a real system by using a newly proposed unbiased evaluation methodology [17]. Through extensive experiments we quantify the tradeoff between different objectives under various constraints. Our experimental results show interesting characteristics of different formulations and our findings may provide valuable guidance to the design of recommendation engines for web portals.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 ClickShapingtoOptimizeMultipleO	Bee-Chung Chen Deepak Agarwal Xuanhui Wang Pradheep Elango			Click Shaping to Optimize Multiple Objectives				10.1145/2020408.2020435		2011