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        <title>Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling</title>
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    <abstract>Interactive topic models are powerful tools for those seeking to understand large collections of text. However, existing sampling-based interactive topic modeling approaches scale poorly to large data sets. Anchor methods, which use a single word to uniquely identify a topic, offer the speed needed for interactive work but lack both a mechanism to inject prior knowledge and lack the intuitive semantics needed for user-facing applications. We propose combinations of words as anchors, going beyond existing single word anchor algorithms—an approach we call “Tandem Anchors”. We begin with a synthetic investigation of this approach then apply the approach to interactive topic modeling in a user study and compare it to interactive and non-interactive approaches. Tandem anchors are faster and more intuitive than existing interactive approaches.</abstract>
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%0 Conference Proceedings
%T Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling
%A Lund, Jeffrey
%A Cook, Connor
%A Seppi, Kevin
%A Boyd-Graber, Jordan
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F lund-etal-2017-tandem
%X Interactive topic models are powerful tools for those seeking to understand large collections of text. However, existing sampling-based interactive topic modeling approaches scale poorly to large data sets. Anchor methods, which use a single word to uniquely identify a topic, offer the speed needed for interactive work but lack both a mechanism to inject prior knowledge and lack the intuitive semantics needed for user-facing applications. We propose combinations of words as anchors, going beyond existing single word anchor algorithms—an approach we call “Tandem Anchors”. We begin with a synthetic investigation of this approach then apply the approach to interactive topic modeling in a user study and compare it to interactive and non-interactive approaches. Tandem anchors are faster and more intuitive than existing interactive approaches.
%R 10.18653/v1/P17-1083
%U https://aclanthology.org/P17-1083
%U https://doi.org/10.18653/v1/P17-1083
%P 896-905

Markdown (Informal)

[Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling](https://aclanthology.org/P17-1083) (Lund et al., ACL 2017)

• Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling (Lund et al., ACL 2017)

ACL

• Jeffrey Lund, Connor Cook, Kevin Seppi, and Jordan Boyd-Graber. 2017. Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 896–905, Vancouver, Canada. Association for Computational Linguistics.