UoR-NCL at SemEval-2023 Task 1: Learning Word-Sense and Image Embeddings for Word Sense Disambiguation

被引：0

作者：

Markchom, Thanet ^{[1
]}

Liang, Huizhi ^{[2
]}

Gitau, Joyce ^{[2
]}

Liu, Zehao ^{[2
]}

Ojha, Varun ^{[2
]}

Taylor, Lee ^{[2
]}

Bonnici, Jake ^{[2
]}

Alshadadi, Abdullah ^{[2
]}

机构：

[1] Univ Reading, Dept Comp Sci, Reading, Berks, England

[2] Newcastle Univ, Sch Comp, Newcastle Upon Tyne, Tyne & Wear, England

来源：

17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023 | 2023年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In SemEval-2023 Task 1, a task of applying Word Sense Disambiguation in an image retrieval system was introduced. To resolve this task, this work proposes three approaches: (1) an unsupervised approach considering similarities between word senses and image captions, (2) a supervised approach using a Siamese neural network, and (3) a self-supervised approach using a Bayesian personalized ranking framework. According to the results, both supervised and self-supervised approaches outperformed the unsupervised approach. They can effectively identify correct images of ambiguous words in the dataset provided in this task.

引用

页码：16 / 22

页数：7

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