EventDNA: a dataset for Dutch news event extraction as a basis for news diversification.

IF 1.7 3区计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Language Resources and Evaluation Pub Date : 2023-01-01 DOI:10.1007/s10579-022-09623-2

Camiel Colruyt, Orphée De Clercq, Thierry Desot, Véronique Hoste

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引用次数: 5

Abstract

News organizations increasingly tailor their news offering to the reader through personalized recommendation algorithms. However, automated recommendation algorithms reflect a commercial logic based on calculated relevance to the user, rather than aiming at a well-informed citizenry. In this paper, we introduce the EventDNA corpus, a dataset of 1773 Dutch-language news articles annotated with information on entities, news events and IPTC Media Topic codes, with the ultimate goal to outline a recommendation algorithm that uses news event diversity rather than previous reading behaviour as a key driver for personalized news recommendation. We describe the EventDNA annotation guidelines, which are inspired by the well-known ERE framework and conclude that it is not practical to apply a fixed event typology such as used in ERE to an unrestricted data context. The corpus and related source code is made available at https://github.com/NewsDNA-LT3/.github.

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EventDNA:荷兰新闻事件提取的数据集，作为新闻多样化的基础。

新闻机构越来越多地通过个性化推荐算法为读者量身定制新闻。然而，自动推荐算法反映了一种基于与用户计算相关性的商业逻辑，而不是针对消息灵通的公民。在本文中，我们介绍了EventDNA语料库，这是一个包含1773篇荷兰语新闻文章的数据集，其中注释了关于实体、新闻事件和IPTC媒体主题代码的信息，最终目标是概述一种推荐算法，该算法使用新闻事件多样性而不是以前的阅读行为作为个性化新闻推荐的关键驱动因素。我们描述了EventDNA注释指南，它受到著名的ERE框架的启发，并得出结论，将固定的事件类型(如ERE中使用的)应用于不受限制的数据上下文是不实际的。语料库和相关源代码可从https://github.com/NewsDNA-LT3/.github获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Language Resources and Evaluation 工程技术-计算机：跨学科应用

CiteScore

6.50

自引率

3.70%

发文量

审稿时长

>12 weeks

期刊介绍： Language Resources and Evaluation is the first publication devoted to the acquisition, creation, annotation, and use of language resources, together with methods for evaluation of resources, technologies, and applications. Language resources include language data and descriptions in machine readable form used to assist and augment language processing applications, such as written or spoken corpora and lexica, multimodal resources, grammars, terminology or domain specific databases and dictionaries, ontologies, multimedia databases, etc., as well as basic software tools for their acquisition, preparation, annotation, management, customization, and use. Evaluation of language resources concerns assessing the state-of-the-art for a given technology, comparing different approaches to a given problem, assessing the availability of resources and technologies for a given application, benchmarking, and assessing system usability and user satisfaction.