Graph-based Dynamic Word Embeddings Article Swipe

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Yuyin Lu , Xin Cheng , Ziran Liang , Yanghui Rao ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.24963/ijcai.2022/594

As time goes by, language evolves with word semantics changing. Unfortunately, traditional word embedding methods neglect the evolution of language and assume that word representations are static. Although contextualized word embedding models can capture the diverse representations of polysemous words, they ignore temporal information as well. To tackle the aforementioned challenges, we propose a graph-based dynamic word embedding (GDWE) model, which focuses on capturing the semantic drift of words continually. We introduce word-level knowledge graphs (WKGs) to store short-term and long-term knowledge. WKGs can provide rich structural information as supplement of lexical information, which help enhance the word embedding quality and capture semantic drift quickly. Theoretical analysis and extensive experiments validate the effectiveness of our GDWE on dynamic word embedding learning.

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Computer Science

Word Embedding

Artificial Intelligence

Knowledge Graph

Theoretical Computer Science

Programming Language

Philosophy

Concepts

Computer science Word (group theory) Embedding Word embedding Natural language processing Artificial intelligence Semantics (computer science) Graph Knowledge graph Theoretical computer science Linguistics Programming language Philosophy

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Type: article
Language: en
Landing Page: https://doi.org/10.24963/ijcai.2022/594
PDF: https://www.ijcai.org/proceedings/2022/0594.pdf
OA Status: bronze
Cited By: 1
References: 55
Related Works: 10
OpenAlex ID: https://openalex.org/W3217011468

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OpenAlex ID: https://openalex.org/W3217011468

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DOI: https://doi.org/10.24963/ijcai.2022/594

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Title: Graph-based Dynamic Word Embeddings

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Type: article

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Language: en

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Publication year: 2022

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Publication date: 2022-07-01

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Authors: Yuyin Lu, Xin Cheng, Ziran Liang, Yanghui Rao

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Landing page: https://doi.org/10.24963/ijcai.2022/594

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Concepts: Computer science, Word (group theory), Embedding, Word embedding, Natural language processing, Artificial intelligence, Semantics (computer science), Graph, Knowledge graph, Theoretical computer science, Linguistics, Programming language, Philosophy

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Cited by: 1

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countries_distinct_count	1
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sustainable_development_goals[0].id	https://metadata.un.org/sdg/4
sustainable_development_goals[0].score	0.6499999761581421
sustainable_development_goals[0].display_name	Quality Education
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