Characterising Dataset Search Queries
Characterising Dataset Search Queries
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DOI：
10.1145/3184558.3191597
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Emilia Kacprzak;Laura M. Koesten;J. Tennison;E. Simperl
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文献类型：
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作者：
Emilia Kacprzak;Laura M. Koesten;J. Tennison;E. Simperl
在网络上生成和发布的数据量正在迅速增加，但在网络上搜索结构化数据仍然存在挑战。在本文中，我们探索数据集搜索通过分析专门为这项工作产生的查询，通过众包实验，并将它们与数据门户网站上的查询搜索日志分析进行比较。搜索环境的变化以及我们给人们的任务改变了生成的查询。我们发现，在我们的实验中发出的查询比数据门户上的数据集搜索查询要长得多。它们还包含了七倍多的地理空间和时间信息，更有可能以问题的形式结构。这些见解可用于定制搜索功能，以满足特定的信息需求和数据集搜索的特征。
The amount of data generated and published on the web is increasing rapidly, but search for structured data on the web still presents challenges. In this paper we explore dataset search by analysing queries specifically generated for this work through a crowdsourcing experiment and comparing them to a search log analysis of queries on data portals. The change in search environment together with the task we gave people altered the generated queries. We found that queries issued in our experiment were much longer than search queries for datasets on data portals. They further contained seven times more mentions of geospatial and of temporal information and are more likely to be structured as questions. These insights can be used to tailor search functionalities to the particular information needs and characteristics of dataset search.