微博/推特地质工作者评价与培训语料库的构建与初步分析

J. O. Wallgrün, F. Hardisty, A. MacEachren, M. Karimzadeh, Yiting Ju, Scott Pezanowski
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引用次数: 19

摘要

本文提出了一种地点参考语料库的构建方法,并将该方法应用于地理微博语料库,这将促进微博/推特地理分析和地理信息检索领域的研究和发展。我们的语料库目前包含6000条带有已识别和地理参考的地名的推文。30%的推文至少包含一个地名。该语料库的目的是支持地质工作者的评价、比较和培训。我们介绍了我们的语料库构建框架,该框架是为了在微博之外普遍适用而开发的,并解释了我们如何使用众包和地理可视化分析技术来支持相对大型语料库的构建。然后,我们报告了语料库建设工作,并分析了在我们的众包方法中执行地点识别的非专业人员之间存在分歧的原因。
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Construction and first analysis of a corpus for the evaluation and training of microblog/twitter geoparsers
This article presents an approach to place reference corpus building and application of the approach to a Geo-Microblog Corpus that will foster research and development in the areas of microblog/twitter geoparsing and geographic information retrieval. Our corpus currently consists of 6000 tweets with identified and georeferenced place names. 30% of the tweets contain at least one place name. The corpus is intended to support the evaluation, comparison, and training of geoparsers. We introduce our corpus building framework, which is developed to be generally applicable beyond microblogs, and explain how we use crowdsourcing and geovisual analytics technology to support the construction of relatively large corpora. We then report on the corpus building work and present an analysis of causes of disagreement between the lay persons performing place identification in our crowdsourcing approach.
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Construction and first analysis of a corpus for the evaluation and training of microblog/twitter geoparsers Improving wikipedia-based place name disambiguation in short texts using structured data from DBpedia Indirect location recommendation Estimating the semantic type of events using location features from Flickr Characterization of toponym usages in texts
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