TSMO 2018

Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth

in conjunction with The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018)

In recent years two sided marketplaces have emerged as viable business models in many real world applications. In particular, we have moved from the social network paradigm to a network with two distinct types of participants representing supply and demand of a specific good. Examples industries include but are not limited to accommodation (Airbnb, Booking.com, HomeAway), video content (YouTube, Dailymotion), Ridesharing (Uber, Didi, Lyft), online shops (Etsy, Ebay), music (Soundcloud), app stores (Apple App Store, Google App Store) and job sites (LinkedIn).

The traditional research in most of these industries focused on satisfying the demand. OTAs would sell hotel accommodation, TV networks would broadcast their own content or taxi companies would own their own vehicle fleet. In modern examples like Airbnb, YouTube or Uber the platforms have customers on the supply side as well, and have to optimize their models taking into consideration host preferences, youtube producers and drivers.

The objective of this workshop is to bring practitioners of two-sided marketplaces together and discuss the evolution of ranking, recommendation, matching and growth data mining to account for the dual nature of the problem.

Registration link: http://www.wsdm-conference.org/2018/attending.html

Day-5 Registration Only (Workshop Day) early registration is $150


9:00 Introduction and Welcome

9:05 Happy for Two (or Three): Joint Revenue Optimization for 2-Sided Parties for Promoted Listings at Etsy

Liangjie Hong, Head of Data Science Etsy

9:50 Impact of free app promotion on future sales: A case study on Amazon Appstore

Harshal A. Chaudhari and John Byers Boston University

10:10 Shaping the future of two-sided e-health markets: Moving developing from research to deployment to market

Vivian Vimarlund, Nicolas Nikula and Craig Kuziemsky Linköping University & University of Ottawa

10:30 Break

11:00 An Overview of Surge Pricing

Hamid Nazerzadeh, Research Scientist Uber

11:45 Spatio-Temporal Pricing for Ridesharing Platforms

Hongyao Ma, Fei Fang and David C. Parkes, Carnegie Mellon University & Harvard SEAS

12:05 Dynamic Pricing in High-dimensions

Adel Javanmard and Hamid Nazerzadeh, University of Southern California & Uber

12:25 Lunch Break

13:45 Search, Pricing and Marketplace Dynamics at Airbnb

Bar Ifrach, Director of Data Science Homes Airbnb

14:45 Pointwise learning to rank for two-sided market platforms

Toma Gulea, Turo

15:05 Coffee Break

15:20 A Smart Instant Book Filter Model based on Dual-Objective Optimization

Yi Hou and Li Fan, Airbnb

15:40 Learning to Match

Themis Mavridis, Pablo Estevez and Lucas Bernardi Booking.com

16:00 Supporting content decisions with Machine Learning @ Netflix

Kelly Uphoff, Vice President, Content and Marketing Science and Analytics at Netflix

Call for Papers

Submission Website

Papers must be submitted in PDF according to the ACM format published in ACM guidelines, selecting the generic "sigconf" sample. Submissions should not exceed 8 pages plus up to one additional page of references.


Submission - November 28, 2017

Extended Submission - December 6, 2017

Decision - December 16, 2017

Camera-ready - January 15, 2018

Workshop - February 9, 2018

The topics of this workshop include, but not limit to, the following:

  • Search in two-sided marketplaces
  • Matching and Personalization in two-sided marketplaces
  • Growth and Monetization for two-sided marketplaces
  • Marketing Strategies
  • Recommendation Systems
  • Dynamic Pricing and Price Recommendations
  • Fraud Detection
  • Fake-content Detection
  • Privacy-preserving Recommendations
  • Experience with deployed systems
  • Learning to Rank
  • Content Ranking in two-sided marketplaces
  • User lifetime value modeling
  • Churn prediction