Searching Documents with Text and Mathematical Content Using a Pen-Based Interface

使用基于笔的界面搜索包含文本和数学内容的文档

• 批准号: 539433-2019
• 负责人: Labahn, George
• 金额: $ 8.32万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=699558
• 关键词: Searching; Documents; Text; Mathematical; Content

Scientific and engineering documents typically contain both text and mathematics. However, when it comes to searching such documents, current commercial technology is able to match text only and so is not well-suited for tasks such as finding mathematical expressions; this must be extended to become math-aware. In this proposal we aim to search text and mathematical content together in order to get the best search results. It has been shown that search engines become more effective when they are able to infer some semantics for terms appearing in documents since, in such instances, terms with similar meanings can be matched. As a result we wish to ensure that math-aware search can infer semantics for mathematical formulas. In this way retrieval based on both text and mathematical formulas can become more effective. In order for a math-aware search engine to have broad impact, it is important that a user be able to enter their mathematical formulas in a natural handwritten manner rather than to use one-dimensional LaTeX-like commands. This can be natural on today's pen-based devices and so an important part of our project is to investigate how a pen-based interface can be used to retrieve documents that are rich in mathematical content. Converting handwritten mathematical expressions to be used in a math-aware search system has considerable difficulties. Challenges include recognition of individual characters, combining handwritten characters into math expressions, distinguishing among similar looking expressions, use of gestures, and determining wild cards. We plan to investigate data-driven methods to ensure good recognition of handwritten math. The implementation and evaluation of our math-aware retrieval system plays a central role in our work.

科学和工程文档通常包含文本和数学。 然而，当涉及到搜索此类文档时，当前的商业技术只能匹配文本，因此不适合查找数学表达式等任务;必须扩展到数学感知。在这个建议中，我们的目标是搜索文本和数学内容在一起，以获得最佳的搜索结果。 它已被证明，搜索引擎变得更加有效，当他们能够推断出一些语义出现在文档中的术语，因为在这种情况下，具有相似的含义的术语可以匹配。 因此，我们希望确保数学感知搜索可以推断数学公式的语义。通过这种方式，基于文本和数学公式的检索可以变得更加有效。 为了使数学感知搜索引擎具有广泛的影响力，重要的是用户能够以自然的手写方式输入他们的数学公式，而不是使用一维的类LaTeX命令。这在今天的基于笔的设备上是很自然的，因此我们项目的一个重要部分是研究如何使用基于笔的界面来检索数学内容丰富的文档。 将手写数学表达式转换为用于数学感知搜索系统具有相当大的困难。挑战包括识别单个字符，将手写字符组合成数学表达式，区分相似的表情，手势的使用以及确定通配符。我们计划研究数据驱动的方法，以确保手写数学的良好识别。 我们的数学感知检索系统的实施和评估在我们的工作中起着核心作用。