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Automatic Task Completion Flows from Web APIs

Published:18 July 2019Publication History

ABSTRACT

The Web contains many APIs that could be combined in countless ways to enable Intelligent Assistants to complete all sorts of tasks. We propose a method to automatically produce task completion flows from a collection of these APIs by combining them in a graph and automatically extracting paths from the graph for task completion. These paths chain together API calls and use the output of executed APIs as inputs to others. We automatically extract these paths from an API graph in response to a user query and then rank the paths by the likelihood of them leading to user satisfaction. We apply our approach for task completion in the email and calendar domains and show how it can be used to automatically create task completion flows.

References

  1. Antoine Bordes, Y-Lan Boureau, and Jason Weston. 2016. Learning end-to-end goal-oriented dialog. arXiv preprint arXiv:1605.07683 (2016).Google ScholarGoogle Scholar
  2. Paul Crook and Alex Marin. 2017. Sequence to Sequence Modeling for User Simulation in Dialog Systems. In Interspeech '17.Google ScholarGoogle ScholarCross RefCross Ref
  3. Paul A. Crook, Alex Marin, Vipul Agarwal, Samantha Anderson, Ohyoung Jang, Aliasgar Lanewala, Karthik Tangirala, and Imed Zitouni. 2018. Conversational Semantic Search: Looking Beyond Web Search, Q&A and Dialog Systems. In WSDM '18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Adi Botea et al. 2019. Generating Dialogue Agents Via Automated Planning. In DEEPDIAL '10.Google ScholarGoogle Scholar
  5. John Lafferty and Chengxiang Zhai. 2001. Document language models, query models, and risk minimization for information retrieval. In SIGIR '01. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, and Asli Celikyilmaz. 2017. Investigation of Language Understanding Impact for Reinforcement Learning Based Dialogue Systems. arXiv preprint arXiv:1703.07055 (2017).Google ScholarGoogle Scholar
  7. Jason D Williams, Kavosh Asadi, and Geoffrey Zweig. 2017. Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. In ACL '17.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Automatic Task Completion Flows from Web APIs

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      • Published in

        cover image ACM Conferences
        SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
        July 2019
        1512 pages
        ISBN:9781450361729
        DOI:10.1145/3331184

        Copyright © 2019 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 18 July 2019

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        • short-paper

        Acceptance Rates

        SIGIR'19 Paper Acceptance Rate84of426submissions,20%Overall Acceptance Rate792of3,983submissions,20%

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