Coupled-Tensor Generated Word Embeddings and Their Composition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00367813" target="_blank" >RIV/68407700:21230/23:00367813 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-37717-4_49" target="_blank" >https://doi.org/10.1007/978-3-031-37717-4_49</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-37717-4_49" target="_blank" >10.1007/978-3-031-37717-4_49</a>
Alternative languages
Result language
angličtina
Original language name
Coupled-Tensor Generated Word Embeddings and Their Composition
Original language description
Contemporary methods of computing vector-space embeddings of words are able to accurately capture both their semantic and syntactic properties. Methods for computing n-gram embeddings do, however, come with downsides. They either require high resources during training or estimation, or come with other disadvantages, such as loss of information about individual positions of words in phrases. We propose two novel approaches to training word vectors enabling a composition of word embeddings into n-gram embeddings. Both methods are based on coupled CP decomposition of tensors that are generated by a sequence of time-shifted word embeddings. We compare our methods with SGNS and show that they provide superior performance on word-analogy tasks.
Czech name
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Czech description
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Classification
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)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Networks and Systems
ISBN
978-3-031-37716-7
ISSN
2367-3370
e-ISSN
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Number of pages
15
Pages from-to
753-767
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Londýn
Event date
Jun 22, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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