Enriching Word Embeddings with Temporal and Spatial Information

Hongyu Gong, Suma Bhat, Pramod Viswanath

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

The meaning of a word is closely linked to sociocultural factors that can change over time and location, resulting in corresponding meaning changes. Taking a global view of words and their meanings in a widely used language, such as English, may require us to capture more refined semantics for use in time-specific or location-aware situations, such as the study of cultural trends or language use. However, popular vector representations for words do not adequately include temporal or spatial information. In this work, we present a model for learning word representation conditioned on time and location. In addition to capturing meaning changes over time and location, we require that the resulting word embeddings retain salient semantic and geometric properties. We train our model on time- and location-stamped corpora, and show using both quantitative and qualitative evaluations that it can capture semantics across time and locations. We note that our model compares favorably with the state-of-the-art for time-specific embedding, and serves as a new benchmark for location-specific embeddings.

Original languageEnglish (US)
Title of host publicationCoNLL 2020 - 24th Conference on Computational Natural Language Learning, Proceedings of the Conference
EditorsRaquel Fernandez, Tal Linzen
PublisherAssociation for Computational Linguistics (ACL)
Pages1-11
Number of pages11
ISBN (Electronic)9781952148637
StatePublished - 2020
Externally publishedYes
Event24th Conference on Computational Natural Language Learning, CoNLL 2020 - Virtual, Online
Duration: Nov 19 2020Nov 20 2020

Publication series

NameCoNLL 2020 - 24th Conference on Computational Natural Language Learning, Proceedings of the Conference

Conference

Conference24th Conference on Computational Natural Language Learning, CoNLL 2020
CityVirtual, Online
Period11/19/2011/20/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language

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