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Uncovering Hidden Structure in Sequence Data via Threading Recurrent Models

Manzil Zaheer
Manzil Zaheer
Amr Ahmed
Amr Ahmed
Yuan Wang
Yuan Wang
Daniel Silva
Daniel Silva
Marc Najork
Marc Najork
Yuchen Wu
Yuchen Wu
Shibani Sanan
Shibani Sanan
Surojit Chatterjee
Surojit Chatterjee

WSDM, pp. 186-194, 2019.

Cited by: 0|Bibtex|Views141|DOI:https://doi.org/10.1145/3289600.3291036
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com
Keywords:
sequence clustering interpretable recurrent neural network topic models

Abstract:

Long Short-Term Memory (LSTM) is one of the most powerful sequence models for user browsing history \citetan2016improved,korpusik2016recurrent or natural language text \citemikolov2010recurrent.Despite the strong performance, it has not gained popularity for user-facing applications, mainly owing to a large number of parameters and lack o...More

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