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Structured Embedding Models for Grouped Data

Author

Listed:
  • Rudolph, Maja

    (Columbia University)

  • Ruiz, Francisco

    (University of Cambridge)

  • Athey, Susan

    (Stanford University)

  • Blei, David

    (Stanford University)

Abstract

Word embeddings are a powerful approach for analyzing language, and exponential family embeddings (EFE) extend them to other types of data. Here we develop structured exponential family embeddings (S-EFE), a method for discovering embeddings that vary across related groups of data. We study how the word usage of U.S. Congressional speeches varies across states and party affiliation, how words are used differently across sections of the ArXiv, and how the co-purchase patterns of groceries can vary across seasons. Key to the success of our method is that the groups share statistical information. We develop two sharing strategies: hierarchical modeling and amortization. We demonstrate the benefits of this approach in empirical studies of speeches, abstracts, and shopping baskets. We show how S-EFE enables group-specific interpretation of word usage, and outperforms EFE in predicting held-out data.

Suggested Citation

  • Rudolph, Maja & Ruiz, Francisco & Athey, Susan & Blei, David, 2017. "Structured Embedding Models for Grouped Data," Research Papers repec:ecl:stabus:3597, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:repec:ecl:stabus:3597
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    File URL: https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/442661
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    Cited by:

    1. Knox, George & Datta, Hannes, 2020. "Streaming Services and the Homogenization of Music Consumption," Other publications TiSEM 0e4d6202-dcc5-4834-ba93-a, Tilburg University, School of Economics and Management.
    2. van Loon, Austin, 2022. "Three Families of Automated Text Analysis," SocArXiv htnej, Center for Open Science.
    3. André Greiner-Petter & Abdou Youssef & Terry Ruas & Bruce R. Miller & Moritz Schubotz & Akiko Aizawa & Bela Gipp, 2020. "Math-word embedding in math search and semantic extraction," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 3017-3046, December.

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