The Importance of Clustering in Word-Sense Induction

This electronic document is a "live" template and already We propose a novel spatial clustering score to evaluate word-sense clusters in for word-sense induction. The score is then evaluated using a basic word-sense induction-pipeline, containing a generally trained Word2Vec model and few...

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Bibliographic Details
Published in2024 14th International Conference on Advanced Computer Information Technologies (ACIT) pp. 735 - 738
Main Authors Reisinger, Johannes, Fischer, Andreas, Goller, Christoph
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.09.2024
Subjects
clustering
DBSCAN
Encyclopedias
Information technology
Internet
Noise
Online services
Optimization
Pipelines
SemEval-2010 Task 14
Transformers
word-sense induction
Word2Vec
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Summary:This electronic document is a "live" template and already We propose a novel spatial clustering score to evaluate word-sense clusters in for word-sense induction. The score is then evaluated using a basic word-sense induction-pipeline, containing a generally trained Word2Vec model and few selected adjustments, focused on cluster evaluation. We overhauled the former parameter score and propose the novel spatial clustering score to evaluate density-based spatial clujstering of applications with noise clusters and provide automatic parameter selection. Our method was evaluated on the SemEval 2010 Task 14 dataset, achieving results en-par with the state-of-the-art
ISSN:2770-5226
DOI:10.1109/ACIT62333.2024.10712629