Extending Word2Vec with Domain-Specific Labels

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F22%3A10250379" target="_blank" >RIV/61989100:27510/22:10250379 - isvavai.cz</a>

Result on the web

<a href="https://annals-csis.org/Volume_30/" target="_blank" >https://annals-csis.org/Volume_30/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Extending Word2Vec with Domain-Specific Labels

Original language description

Choosing a proper representation of textual data isan important part of natural language processing. One option is using Word2Vec embeddings, i.e., dense vectors whose properties can to a degree capture the &quot;meaning&quot; of each word. One of the main disadvantages of Word2Vec is its inability to distinguish between antonyms. Motivated by this deficiency, this paper presents a Word2Vec extension for incorporating domain-specific labels. The goal is to improve the ability to differentiate between embeddings of words associated with different document labels or classes. This improvement is demonstrated on word embeddings derived from tweets related to a publicly traded company. Each tweet is given a label depending on whether its publication coincides with a stock price increase or decrease. The extended Word2Vec model then takes this label into account. The user can also set the weight of this label in the embedding creation process. Experiment results show that increasing this weight leads to a gradual decrease in cosine similarity between embeddings of words associated with different labels. This decrease in similarity can be interpreted as an improvement of the ability to distinguish between these words.

Czech name

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Czech description

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Type

D - Article in proceedings

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

2022

Confidentiality

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

Article name in the collection

Annals of Computer Science and Information Systems. Volume 30

ISBN

978-83-965897-1-2

ISSN

2300-5963

e-ISSN

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Number of pages

4

Pages from-to

157-160

Publisher name

Polskie Towarzystwo Informatyczne

Place of publication

Varšava

Event location

Sofie

Event date

Sep 4, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000904404400022