Facilitating Document Reading by Linking Text and Tables
Facilitating Document Reading by Linking Text and Tables
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DOI：
10.1145/3242587.3242617
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Dae Hyun Kim;Enamul Hoque;Juho Kim;Maneesh Agrawala
中科院分区：
文献类型：
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作者：
Dae Hyun Kim;Enamul Hoque;Juho Kim;Maneesh Agrawala
文档作者通常使用表支持文本中介绍的参数。但是，由于桌子通常与主体文本分开，因此读者必须在文档的不同部分之间将注意力分开。我们提出了一个交互式文档读取器，该文档读取器将自动将文档文本与相应的表单元单元联系起来。读者可以选择一个句子（或表格单元格），而我们的读者可以突出显示相关的表单元格（或句子）。我们为现有的PDF文档中提取句子文本和表单元之间提取此类参考的自动管道，该文本将表与自然语言处理和基于规则的匹配结合在一起。在330（句子，表）对的测试语料库中，我们的管道正确提取了48.8％的参考文献。另外30.5％的人仅包含假阴性（FN）错误 - 参考缺失表单元。其余的20.7％包含假阳性（FP）错误 - 参考包括外部表单元，因此可能会误导读者。一项用户研究发现，尽管有这样的错误，但我们的交互式文档阅读器可帮助读取器与基准文档读取器更准确，更快地匹配相应的表单元格。
Document authors commonly use tables to support arguments presented in the text. But, because tables are usually separate from the main body text, readers must split their attention between different parts of the document. We present an interactive document reader that automatically links document text with corresponding table cells. Readers can select a sentence (or tables cells) and our reader highlights the relevant table cells (or sentences). We provide an automatic pipeline for extracting such references between sentence text and table cells for existing PDF documents that combines structural analysis of tables with natural language processing and rule-based matching. On a test corpus of 330 (sentence, table) pairs, our pipeline correctly extracts 48.8% of the references. An additional 30.5% contain only false negatives (FN) errors -- the reference is missing table cells. The remaining 20.7% contain false positives (FP) errors -- the reference includes extraneous table cells and could therefore mislead readers. A user study finds that despite such errors, our interactive document reader helps readers match sentences with corresponding table cells more accurately and quickly than a baseline document reader.