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Crowdsourcing interactions: using crowdsourcing for evaluating interactive information retrieval systems

机译:众包互动:使用众包评估交互式信息检索系统

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摘要

In the field of information retrieval (IR), researchers and practitioners are often faced with a demand for valid approaches to evaluate the performance of retrieval systems. The Cranfield experiment paradigm has been dominant for the in-vitro evaluation of IR systems. Alternative to this paradigm, laboratory-based user studies have been widely used to evaluate interactive information retrieval (IIR) systems, and at the same time investigate users' information searching behaviours. Major drawbacks of laboratory-based user studies for evaluating IIR systems include the high monetary and temporal costs involved in setting up and running those experiments, the lack of heterogeneity amongst the user population and the limited scale of the experiments, which usually involve a relatively restricted set of users. In this paper, we propose an alternative experimental methodology to laboratory-based user studies. Our novel experimental methodology uses a crowdsourcing platform as a means of engaging study participants. Through crowdsourcing, our experimental methodology can capture user interactions and searching behaviours at a lower cost, with more data, and within a shorter period than traditional laboratory-based user studies, and therefore can be used to assess the performances of IIR systems. In this article, we show the characteristic differences of our approach with respect to traditional IIR experimental and evaluation procedures. We also perform a use case study comparing crowdsourcing-based evaluation with laboratory-based evaluation of IIR systems, which can serve as a tutorial for setting up crowdsourcing-based IIR evaluations.
机译:在信息检索(IR)领域,研究人员和从业人员经常面临对评估检索系统性能的有效方法的需求。 Cranfield实验范式在红外系统的体外评估中占主导地位。除此范例外,基于实验室的用户研究已广泛用于评估交互式信息检索(IIR)系统,同时调查用户的信息搜索行为。基于实验室的用户研究用于评估IIR系统的主要弊端包括建立和运行这些实验所涉及的高昂金钱和时间成本,用户群体之间缺乏异质性以及实验规模有限(通常涉及相对有限)用户集。在本文中,我们提出了一种替代基于实验室的用户研究的实验方法。我们新颖的实验方法利用众包平台作为吸引研究参与者的一种手段。与传统的基于实验室的用户研究相比,通过众包,我们的实验方法可以以较低的成本,更多的数据和更短的时间捕获用户交互和搜索行为,因此可用于评估IIR系统的性能。在本文中,我们展示了我们的方法相对于传统IIR实验和评估程序的特征差异。我们还将执行一个用例研究,将基于众包的评估与基于实验室的IIR系统评估进行比较,这可以作为建立基于众包的IIR评估的教程。

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