利用事后解释与比较设计增强文本语料库探索
Enhancing Text Corpus Exploration with Post Hoc Explanations and Comparative Design
AI总结：
本文提出结合事后显著性解释与多尺度比较视图的 TCE 工具增强方法，并通过原型与用户研究验证其可灵活支持论文摘要和报纸档案的多元探索任务。
摘要：
文本语料库探索（TCE）涵盖一系列探索式搜索任务：它超越简单检索，还包括条目发现以及了解语料库和主题。系统通过基于相似性的推荐和基于嵌入的空间地图等工具支持 TCE。然而，这些工具只处理特定任务；当前系统缺乏足够的灵活性，无法支持实践中遇到的各类任务，以及用户采用的迭代式、多尺度工作流。在本文中，我们提出若干方法，利用事后解释和多尺度、比较式设计增强 TCE 工具，以灵活支持用户需求。我们引入显著性函数，作为一种对相似性、推荐和空间布局提供事后解释的机制。这种事后策略使我们的方法能够补充多种底层算法；显著性函数在从单个文档到整个语料库的各个尺度上，同时提供基于范例和基于特征的解释。这些解释被整合进一组在多个尺度上运行的视图中。这些视图使用明确支持比较的设计元素，以实现灵活集成。它们共同构成一种方法，提供可处理一系列任务的灵活工具集。我们在一个原型系统中演示了该方法，该系统支持探索论文摘要语料库和报纸档案。示例说明了我们的方法如何使系统灵活支持用户场景中出现的广泛任务和工作流。一项用户研究证实，研究人员能够使用我们的系统完成多种任务。
英文摘要：
Text corpus exploration (TCE) spans the range of exploratory search tasks: it goes beyond simple retrieval to include item discovery and learning about the corpus and topic. Systems support TCE with tools such as similarity-based recommendations and embedding-based spatial maps. However, these tools address specific tasks; current systems lack the flexibility to support the range of tasks encountered in practice and the iterative, multiscale, workflows users employ. In this paper, we provide methods that enhance TCE tools with post hoc explanations and multiscale, comparative designs to provide flexible support for user needs. We introduce salience functions as a mechanism to provide post hoc explanations of similarity, recommendations, and spatial placement. This post hoc strategy allows our approach to complement a variety of underlying algorithms; the salience functions provide both exemplar- and feature-based explanations at scales ranging from individual documents through to the entire corpus. These explanations are incorporated into a set of views that operate at multiple scales. The views use design elements that explicitly support comparison to enable flexible integration. Together, these form an approach that provides a flexible toolset that can address a range of tasks. We demonstrate our approach in a prototype system that enables the exploration of corpora of paper abstracts and newspaper archives. Examples illustrate how our approach enables the system to flexibly support a wide range of tasks and workflows that emerge in user scenarios. A user study confirms that researchers are able to use our system to achieve a variety of tasks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
