A method for constructing word sense embeddings based on word sense induction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10254662" target="_blank" >RIV/61989100:27240/23:10254662 - isvavai.cz</a>

Result on the web

<a href="https://www.nature.com/articles/s41598-023-40062-3" target="_blank" >https://www.nature.com/articles/s41598-023-40062-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-023-40062-3" target="_blank" >10.1038/s41598-023-40062-3</a>

Result language

angličtina

Original language name

A method for constructing word sense embeddings based on word sense induction

Original language description

Polysemy is an inherent characteristic of natural language. In order to make it easier to distinguish between different senses of polysemous words, we propose a method for encoding multiple different senses of polysemous words using a single vector. The method first uses a two-layer bidirectional long short-term memory neural network and a self-attention mechanism to extract the contextual information of polysemous words. Then, a K-means algorithm, which is improved by optimizing the density peaks clustering algorithm based on cosine similarity, is applied to perform word sense induction on the contextual information of polysemous words. Finally, the method constructs the corresponding word sense embedded representations of the polysemous words. The results of the experiments demonstrate that the proposed method produces better word sense induction than Euclidean distance, Pearson correlation, and KL-divergence and more accurate word sense embeddings than mean shift, DBSCAN, spectral clustering, and agglomerative clustering. (C) 2023, Springer Nature Limited.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientific Reports

ISSN

2045-2322

e-ISSN

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Volume of the periodical

13

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

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UT code for WoS article

001045574100067

EID of the result in the Scopus database

2-s2.0-85167532342