Google Research

ShopTalk: A System for Conversational Faceted Search

  • Bhargav Kanagal
  • D. Sivakumar
  • Ebenezer Omotola Anjorin
  • Gurmeet Singh Manku
  • Ilya Eckstein
  • James Patrick Lee-Thorp
  • Jim Rosswog
  • Jingchen Feng
  • Joshua Ainslie
  • Larry Adams
  • Michael Anthony Pohl
  • Sudeep Gandhe
  • Sumit Kumar Sanghai
  • Zach Pearson
SIGIR eCom '22 (2022)


We present ShopTalk, a multi-turn conversational faceted search system for Shopping that is designed to handle large and complex schemas that are beyond the scope of state of the art slot-filling systems. ShopTalk decouples dialog management from fulfillment, thereby allowing the dialog understanding system to be domain-agnostic and not tied to the particular Shopping application. The dialog understanding system consists of a deep-learned Contextual Language Understanding module, which interprets user utterances, and a primarily rules-based Dialog-State Tracker (DST), which updates the dialog state and formulates search requests intended for the fulfillment engine. The interface between the two modules consists of a minimal set of domain-agnostic ``intent operators,'' which instruct the DST on how to update the dialog state. ShopTalk was deployed in 2020 on the Google Assistant for Shopping searches.

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