Automated Support for Collective Memory of Conversational Interactions

Authors

  • Walter Lasecki University of Rochester
  • Jeffrey Bigham Carnegie Mellon University

DOI:

https://doi.org/10.1609/hcomp.v1i1.13104

Keywords:

Real-Time Crowdsourcing, Conversational Interaction, Collective Memory

Abstract

Maintaining consistency is a difficult challenge in crowd-powered systems in which constituent crowd workers may change over time. We discuss an initial outline for Chorus:Mnemonic, a system that augments the crowd's collective memory of a conversation by automatically recovering past knowledge based on topic, allowing the system to support consistent multi-session interactions. We present the design of the system itself, and discuss methods for testing its effectiveness. Our goal is to provide consistency between long interactions with crowd-powered conversational assistants by using AI to augment crowd workers.

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Published

2013-11-03

How to Cite

Lasecki, W., & Bigham, J. (2013). Automated Support for Collective Memory of Conversational Interactions. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 1(1), 40-41. https://doi.org/10.1609/hcomp.v1i1.13104

Issue

Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing

Section

Works in Progress