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Visual Exploration of Neural Document Embedding in Information Retrieval: Semantics and Feature Selection

机译:信息检索信息中嵌入神经文献的视觉探索:语义与特征选择

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摘要

Neural embeddings are widely used in language modeling and feature generation with superior computational power. Particularly, neural document embedding - converting texts of variable-length to semantic vector representations - has shown to benefit widespread downstream applications, e.g., information retrieval (IR). However, the black-box nature makes it difficult to understand how the semantics are encoded and employed. We propose visual exploration of neural document embedding to gain insights into the underlying embedding space, and promote the utilization in prevalent IR applications. In this study, we take an IR application-driven view, which is further motivated by biomedical IR in healthcare decision-making, and collaborate with domain experts to design and develop a visual analytics system. This system visualizes neural document embeddings as a configurable document map and enables guidance and reasoning; facilitates to explore the neural embedding space and identify salient neural dimensions (semantic features) per task and domain interest; and supports advisable feature selection (semantic analysis) along with instant visual feedback to promote IR performance. We demonstrate the usefulness and effectiveness of this system and present inspiring findings in use cases. This work will help designers/developers of downstream applications gain insights and confidence in neural document embedding, and exploit that to achieve more favorable performance in application domains.
机译:神经嵌入式广泛用于语言建模和功能生成,具有卓越的计算能力。特别地,嵌入 - 将可变长度的文本转换为语义矢量表示 - 已经显示为有利于广泛的下游应用,例如信息检索(IR)。然而,黑匣子的性质使得难以理解语义是如何编码和使用的。我们提出了对神经文件嵌入的视觉探索,以获得对潜在的嵌入空间的见解,并促进普遍存在的IR应用中的利用。在这项研究中,我们采用IR应用程序驱动的视图,该视图是由生物医学IR进一步激励的医疗保健决策,并与域专家合作设计和开发视觉分析系统。该系统可视化神经文档嵌入式作为可配置文件地图,并实现指导和推理;有助于探索神经嵌入空间,并确定每个任务和领域兴趣的突出神经维度(语义特征);并支持可建议的功能选择(语义分析)以及即时视觉反馈,以促进IR性能。我们展示了该系统的有用性和有效性,并在使用情况下呈现了鼓舞人心的发现。这项工作将有助于设计人员/开发人员的下游应用程序在神经文件嵌入的洞察力和信心中,并利用这一点在应用领域中实现更有利的性能。

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