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Multilingual Topic Labelling of News Topics using Ontological Mapping ...
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Abstract:
The large volume of news produced daily makes topic modelling useful for analysing topical trends. A topic is usually represented by a ranked list of words but this can be dicult and time-consuming for humans to interpret. Therefore, various methods have been proposed to generate labels that capture the semantic content of a topic. However, there has been no work so far on coming up with multilingual labels which can be useful for exploring multilingual news collections. We propose an ontological mapping method that maps topics to concepts in a language-agnostic news ontology. We test our method on Finnish and English topics and show that it performs on par with state-of-the-art label generation methods, is able to produce multilingual labels, and can be applied to topics from languages that have not been seen during training without any modifications. ...
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Keyword:
topic labelling, ontology linking, cross-lingual embeddings
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URL: https://dx.doi.org/10.5281/zenodo.6334491 https://zenodo.org/record/6334491
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Multilingual Topic Labelling of News Topics using Ontological Mapping ...
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EMBEDDIA at SemEval-2022 Task 8: Investigating Sentence, Image, and Knowledge Graph Representations for Multilingual News Article Similarity ...
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EMBEDDIA at SemEval-2022 Task 8: Investigating Sentence, Image, and Knowledge Graph Representations for Multilingual News Article Similarity ...
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Not All Comments Are Equal: Insights into Comment Moderation from a Topic-aware Model ...
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Not All Comments Are Equal: Insights into Comment Moderation from a Topic-aware Model ...
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Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model ...
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Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model ...
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Not all comments are equal: Insights into comment moderation from a topic-aware model ...
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Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model ...
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Not all comments are equal: Insights into comment moderation from a topic-aware model ...
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Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings not Always Better Than Static for Semantic Change Detection ...
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Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings not Always Better Than Static for Semantic Change Detection ...
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A Comparison of Unsupervised Methods for Ad hoc Cross-Lingual Document Retrieval ...
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A Comparison of Unsupervised Methods for Ad hoc Cross-Lingual Document Retrieval ...
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A Comparison of Unsupervised Methods for Ad hoc Cross-Lingual Document Retrieval ...
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A Comparison of Unsupervised Methods for Ad hoc Cross-Lingual Document Retrieval ...
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The expansion of isms, 1820–1917: Data-driven analysis of political language in digitized newspaper collections ...
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The expansion of isms, 1820–1917: Data-driven analysis of political language in digitized newspaper collections ...
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