Unsupervised Few-Bits Semantic Hashing with Implicit Topics Modeling

Fanghua Ye, Jarana Manotumruksa, Emine Yilmaz


Abstract
Semantic hashing is a powerful paradigm for representing texts as compact binary hash codes. The explosion of short text data has spurred the demand of few-bits hashing. However, the performance of existing semantic hashing methods cannot be guaranteed when applied to few-bits hashing because of severe information loss. In this paper, we present a simple but effective unsupervised neural generative semantic hashing method with a focus on few-bits hashing. Our model is built upon variational autoencoder and represents each hash bit as a Bernoulli variable, which allows the model to be end-to-end trainable. To address the issue of information loss, we introduce a set of auxiliary implicit topic vectors. With the aid of these topic vectors, the generated hash codes are not only low-dimensional representations of the original texts but also capture their implicit topics. We conduct comprehensive experiments on four datasets. The results demonstrate that our approach achieves significant improvements over state-of-the-art semantic hashing methods in few-bits hashing.
Anthology ID:
2020.findings-emnlp.233
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2566–2575
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.233
DOI:
10.18653/v1/2020.findings-emnlp.233
Bibkey:
Cite (ACL):
Fanghua Ye, Jarana Manotumruksa, and Emine Yilmaz. 2020. Unsupervised Few-Bits Semantic Hashing with Implicit Topics Modeling. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 2566–2575, Online. Association for Computational Linguistics.
Cite (Informal):
Unsupervised Few-Bits Semantic Hashing with Implicit Topics Modeling (Ye et al., Findings 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.findings-emnlp.233.pdf
Video:
 https://slideslive.com/38940106
Code
 smartyfh/wish