2014 BeyondClicksDwellTimeforPersona

• (Yi et al., 2014) ⇒ Xing Yi, Liangjie Hong, Erheng Zhong, Nanthan Nan Liu, and Suju Rajan. (2014). “Beyond Clicks: Dwell Time for Personalization.” In: Proceedings of the 8th ACM Conference on Recommender systems. ISBN:978-1-4503-2668-1 doi:10.1145/2645710.2645724

Subject Headings: Dwell Time, Online Customer Engagement.

Cited By

• http://scholar.google.com/scholar?q=%222014%22+Beyond+Clicks%3A+Dwell+Time+for+Personalization
• http://dl.acm.org/citation.cfm?id=2645710.2645724&preflayout=flat#citedby

Quotes

Abstract

Many internet companies, such as Yahoo, Facebook, Google and Twitter, rely on content recommendation systems to deliver the most relevant content items to individual users through personalization. Delivering such personalized user experiences is believed to increase the long term engagement of users. While there has been a lot of progress in designing effective personalized recommender systems, by exploiting user interests and historical interaction data through implicit (item click) or explicit (item rating) feedback, directly optimizing for users' satisfaction with the system remains challenging. In this paper, we explore the idea of using item-level dwell time as a proxy to quantify how likely a content item is relevant to a particular user. We describe a novel method to compute accurate dwell time based on client-side and server-side logging and demonstrate how to normalize dwell time across different devices and contexts. In addition, we describe our experiments in incorporating dwell time into state-of-the-art learning to rank techniques and collaborative filtering models that obtain competitive performances in both offline and online settings.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 BeyondClicksDwellTimeforPersona	Erheng Zhong Liangjie Hong Suju Rajan Xing Yi Nanthan Nan Liu			Beyond Clicks: Dwell Time for Personalization				10.1145/2645710.2645724		2014