Improving Retrieval of Unstructured Information using existing Information Structures

使用现有信息结构改进非结构化信息的检索

• 批准号: RGPIN-2014-06292
• 负责人: Julien, CharlesAntoine
• 金额: $ 1.68万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588923
• 关键词: Improving; Retrieval; Unstructured; Information; using

Unstructured information generally refers to text-heavy information that is not organized in a pre-defined manner such as what is found on the Web or in collections of texts. Most developments in unstructured information searching have addressed the technical algorithms for retrieving billions of Web pages; meanwhile, interfaces used for Web searching have not evolved at the same pace. To successfully use current Web searching tools, users must generally possess or acquire the vocabulary used by the authors of the relevant documents, and searchers inevitably encounter information needs that they cannot adequately express using one or two vague and broad keywords that often have multiple meanings. This is the vocabulary mismatch problem that plagues information retrieval systems—especially when searching unfamiliar knowledge domains or subject areas. This research program seeks to develop novel online information searching tools that bridge the gap between organized information (e.g., scientific, library, business or personal information collections) and Web searching. It assumes that searchers seek information to meet their needs, regardless of whether the information is structured (e.g., scientific, library or business information) or unstructured (e.g., Web searching or text). For example, structured information can suggest new keywords to better describe users’ needs. This research program capitalizes on existing information organization investments to complement unstructured information retrieval technologies. It will ensure that the tools are useful and appreciated by recording how test participants use the tools over a period of at least 3 months. Published results will include open-source online search tool prototypes, a testing engine that could be used by other interface designers and researchers, and results of the usability testing over time. This research program is innovative by virtue of the novel search systems it will design and test over time. Firstly, it will integrate existing information organization investments with the ubiquitous keyword searching and ranking in order to improve information discovery. For example, users could search a library catalogue and the Web using one integrated tool instead of two different tools they must currently use. Secondly, the tools will be tested over time to ensure that they meet searchers’ expectations and require little or no training. This type of testing over time is very rare and highly appropriate when the objective is to ensure users can truly use and appreciate a tool beyond its initial novelty. This research aims to support students who are interested in improving information exploration and searching technologies: 88% of the budget is given directly to students (i.e., salaries, travel expenses, and computers). The supported PhD and master’s students will be part of an existing research group where they will have the opportunity to collaborate with other research groups from the School of Information Studies, McGill and the University of Montreal. They will acquire skills in research, software design and development, testing, and oral/written communication, which are valuable in academic and industrial settings. Taken as a whole, this research program has the potential to improve the tools Canadian citizens use to search for all kinds of information by suggesting new keywords, grouping similar information together, and tearing down the artificial boundary between organized information collections (e.g., library catalogues or business taxonomies) and Web searching.

非结构化信息通常是指未以预定义方式组织的文本信息，例如在网络或文本集合中找到的信息。非结构化信息搜索的大多数发展都解决了检索数十亿网页的技术算法。另一方面，用于网络搜索的界面并没有以同样的速度发展，为了成功地使用当前的网络搜索工具，用户通常必须拥有或获取相关文档的作者所使用的词汇，并且搜索者不可避免地遇到信息需求。他们无法用一种语言充分表达或者两个模糊且宽泛的关键字通常具有多种含义，这是困扰信息检索系统的词汇不匹配问题，尤其是在搜索不熟悉的知识领域或主题领域时。 该研究计划旨在开发新颖的在线信息搜索工具，以弥合有组织的信息（例如，科学、图书馆、商业或个人信息集合）和网络搜索之间的差距。它假设搜索者寻求信息来满足他们的需求，无论是否。信息是结构化的（例如，科学、图书馆或商业信息）或非结构化的（例如，网络搜索或文本）。例如，结构化信息可以建议新的关键字以更好地描述用户的需求。它将通过记录测试参与者在至少 3 个月内如何使用这些工具来补充非结构化信息检索技术。发布的结果将包括开源在线搜索工具原型，这是一个可以实现的测试引擎。可供其他界面设计人员和研究人员使用，以及随着时间的推移可用性测试的结果。 该研究计划具有创新性，因为它将随着时间的推移设计和测试新颖的搜索系统，首先，它将把现有的信息组织投资与无处不在的关键词搜索和排名相结合，以改善信息发现。图书馆目录和网络使用一种集成工具，而不是当前必须使用的两种不同工具。 其次，这些工具将随着时间的推移进行测试，以确保它们满足搜索者的期望，并且随着时间的推移，这种类型的测试是很少或不需要的。当目标是确保用户能够真正使用和欣赏工具，超越其最初的新颖性。 这项研究旨在支持有兴趣改进信息探索和搜索技术的学生：88% 的预算直接提供给学生（即工资、差旅费和计算机）。受支持的博士生和硕士生将成为项目的一部分。他们将有机会与麦吉尔信息研究学院和蒙特利尔大学的其他研究小组合作，获得研究、软件设计和开发、测试以及口头/书面交流方面的技能。在学术和工业环境中都很有价值。总体而言，该研究计划有可能通过建议新的关键词、将相似的信息分组在一起以及打破有组织的信息集合（例如图书馆目录）之间的人为界限来改进加拿大公民用来搜索各种信息的工具。或商业分类法）和网络搜索。