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We show how specific choices within this approach lead to different sequential event prediction problems and algorithms

Sequential event prediction

Machine Learning, no. 2-3 (2013): 357-380

Cited by: 25|Views16
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Abstract

In sequential event prediction, we are given a "sequence database" of past event sequences to learn from, and we aim to predict the next event within a current event sequence. We focus on applications where the set of the past events has predictive power and not the specific order of those past events. Such applications arise in recommend...More

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Introduction
  • Sequential event prediction refers to a wide class of problems in which a set of initially hidden events are sequentially revealed.
  • Sequential event prediction
  • Benjamin Letham · Cynthia Rudin · David Madigan
  • Abstract In sequential event prediction, the authors are given a “sequence database” of past event sequences to learn from, and the authors aim to predict the event within a current event sequence.
Highlights
  • Sequential event prediction refers to a wide class of problems in which a set of initially hidden events are sequentially revealed
  • We focus on applications where the set of the past events has predictive power and not the specific order of those past events. Such applications arise in recommender systems, equipment maintenance, medical informatics, and in other domains
  • Our formalization of sequential event prediction draws on ideas from supervised ranking
  • We show how specific choices within this approach lead to different sequential event prediction problems and algorithms
  • The observed sequence of events depends on user choices, which may be influenced by the recommendations, which are themselves tailored to the user’s choices
  • 1 Introduction Sequential event prediction refers to a wide class of problems in which a set of initially hidden events are sequentially revealed
Results
  • The authors focus on applications where the set of the past events has predictive power and not the specific order of those past events.
  • Such applications arise in recommender systems, equipment maintenance, medical informatics, and in other domains.
  • The authors' formalization of sequential event prediction draws on ideas from supervised ranking.
  • The authors show how specific choices within this approach lead to different sequential event prediction problems and algorithms.
  • The observed sequence of events depends on user choices, which may be influenced by the recommendations, which are themselves tailored to the user’s choices.
  • This leads to sequential event prediction algorithms involving a non-convex optimization problem.
  • The authors apply our approach to an online grocery store recommender system, email recipient recommendation, and a novel application in the health event prediction domain.
  • Keywords Sequential event prediction · Supervised ranking · Recommender systems
  • 1 Introduction Sequential event prediction refers to a wide class of problems in which a set of initially hidden events are sequentially revealed.
  • The goal is to use the set of revealed events, but
Conclusion
  • Editors: Eyke Hüllermeier and Johannes Fürnkranz.
  • B. Letham ( ) Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA e-mail: bletham@mit.edu C.
  • Rudin MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA e-mail: rudin@mit.edu D.
  • Madigan Department of Statistics, Columbia University, New York, NY, USA e-mail: madigan@stat.columbia.edu
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