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Finding the right term: Retrieving and exploring semantic concepts in astronomical vocabularies

机译：找到合适的词：检索和探索天文词汇中的语义概念

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摘要

Astronomy, like many domains, already has several sets of terminology in general use, referred to as controlled vocabularies. For example, the keywords for tagging journal articles, or the taxonomy of terms used to label image files. These existing vocabularies can be encoded into skos, a W3C proposed recommendation for representing vocabularies on the Semantic Web, so that computer systems can help users to search for and discover resources tagged with vocabulary concepts. However, this requires a search mechanism to go from a user-supplied string to a vocabulary concept.rnIn this paper, we present our experiences in implementing the Vocabulary Explorer, a vocabulary search service based on the Terrier Information Retrieval Platform. We investigate the capabilities of existing document weighting models for identifying the correct vocabulary concept for a query. Due to the highly structured nature of a skos encoded vocabulary, we investigate the effects of term weighting (boosting the score of concepts that match on particular fields of a vocabulary concept), and query expansion. We found that the existing document weighting models provided very high quality results, but these could be improved further with the use of term weighting that makes use of the semantic evidence.
机译：像许多领域一样，天文学已经有了几套通用的术语，称为受控词汇。例如，用于标记期刊文章的关键字，或用于标记图像文件的术语分类。这些现有词汇可以被编码为skos，这是W3C提出的在语义Web上表示词汇的建议，以便计算机系统可以帮助用户搜索和发现标记有词汇概念的资源。但是，这需要一种从用户提供的字符串到词汇表概念的搜索机制。在本文中，我们将介绍在实现“词汇表资源管理器”（基于Terrier Information Retrieval Platform的词汇表搜索服务）方面的经验。我们研究了现有文档权重模型的功能，这些功能可为查询识别正确的词汇概念。由于skos编码词汇表的高度结构化性质，我们研究了术语加权（提高在词汇表概念的特定字段上匹配的概念的分数）和查询扩展的影响。我们发现现有的文档加权模型提供了非常高质量的结果，但是可以通过使用利用语义证据的术语加权来进一步改善这些结果。

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