Multilingual Embeddings for Clustering Cultural Events

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AR8TWD2E9" target="_blank" >RIV/00216208:11320/22:R8TWD2E9 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-031-16500-9_8" target="_blank" >https://doi.org/10.1007/978-3-031-16500-9_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-16500-9_8" target="_blank" >10.1007/978-3-031-16500-9_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multilingual Embeddings for Clustering Cultural Events

Popis výsledku v původním jazyce

In the present paper we describe our approach to semi-automatic text annotation based on clustering. Given a large collection of announcements of cultural events from several websites, we group them based on their content and infer respective semantic categories that can be used for annotation (e.g. lecture, sports, food, music). We experiment with various models for vectorising the texts, including pretrained multilingual Sentence Transformers and multilingual ELMo models. The produced text embeddings are then clustered using K-means. We evaluate our clustering results using a stratified sample of texts with pre-existing categories (collected from websites listing the events) as well as intrinsic evaluation measures. The rationale behind this work is to produce a single categorisation covering texts from various sources and in two languages - English and Russian. The labelled collection of texts is intended for use in a Digital Humanities project aimed at describing cultural life in a selected location, for example, comparing types of events in Russian and British cities.

Název v anglickém jazyce

Multilingual Embeddings for Clustering Cultural Events

Popis výsledku anglicky

In the present paper we describe our approach to semi-automatic text annotation based on clustering. Given a large collection of announcements of cultural events from several websites, we group them based on their content and infer respective semantic categories that can be used for annotation (e.g. lecture, sports, food, music). We experiment with various models for vectorising the texts, including pretrained multilingual Sentence Transformers and multilingual ELMo models. The produced text embeddings are then clustered using K-means. We evaluate our clustering results using a stratified sample of texts with pre-existing categories (collected from websites listing the events) as well as intrinsic evaluation measures. The rationale behind this work is to produce a single categorisation covering texts from various sources and in two languages - English and Russian. The labelled collection of texts is intended for use in a Digital Humanities project aimed at describing cultural life in a selected location, for example, comparing types of events in Russian and British cities.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

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Návaznosti

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Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Analysis of Images, Social Networks and Texts

ISBN

978-3-031-16500-9

ISSN

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e-ISSN

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Počet stran výsledku

13

Strana od-do

84-96

Název nakladatele

Springer International Publishing

Místo vydání

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Místo konání akce

Cham

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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