A survey on dynamic and stochastic vehicle routing problems

A survey on dynamic and stochastic vehicle routing problems Ritzinger et al., International Journal of Production Research It’s been a while since we last looked at an overview of dynamic vehicle routing problems: that was back in 2014 (See ‘Dynamic vehicle routing, pickup, and delivery problems’). That paper has fond memories for me, I looked … Continue reading A survey on dynamic and stochastic vehicle routing problems

Beyond news contents: the role of social context for fake news detection

Beyond news contents: the role of social context for fake news detection Shu et al., WSDM'19 Today we’re looking at a more general fake news problem: detecting fake news that is being spread on a social network. Forgetting the computer science angle for a minute, it seems intuitive to me that some important factors here … Continue reading Beyond news contents: the role of social context for fake news detection

Automatic discovery of tactics in spatio-temporal soccer match data

Automatic discovery of tactics in spatio-temporal soccer match data Decroos et al., KDD'18 Here’s a fun paper to end the week. Data collection from sporting events is now widespread. This fuels an endless thirst for team and player statistics. In terms of football (which shall refer to the game of soccer throughout this write-up) that … Continue reading Automatic discovery of tactics in spatio-temporal soccer match data

Detecting spacecraft anomalies using LSTMs and nonparametric dynamic thresholding

Detecting spacecraft anomalies using LSTMs and nonparametric dynamic thresholding Hundman et al., KDD'18 How do you effectively monitor a spacecraft? That was the question facing NASA’s Jet Propulsion Laboratory as they looked forward towards exponentially increasing telemetry data rates for Earth Science satellites (e.g., around 85 terabytes/day for a Synthetic Aperture Radar satellite). Spacecraft are … Continue reading Detecting spacecraft anomalies using LSTMs and nonparametric dynamic thresholding

Online parameter selection for web-based ranking problems

Online parameter selection for web-based ranking problems Agarwal et al., KDD'18 Last week we looked at production systems from Facebook, Airbnb, and Snap Inc., today it’s the turned of LinkedIn. This paper describes the system and model that LinkedIn use to determine the items to be shown in a user’s feed: It replaces previous hand-tuning … Continue reading Online parameter selection for web-based ranking problems

I know you’ll be back: interpretable new user clustering and churn prediction on a mobile social application

I know you’ll be back: interpretable new user clustering and churn prediction on a mobile social application Yang et al., KDD'18 Churn rates (how fast users abandon your app / service) are really important in modelling a business. If the churn rate is too high, it’s hard to maintain growth. Since acquiring new customers is … Continue reading I know you’ll be back: interpretable new user clustering and churn prediction on a mobile social application