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经预定方式组织的文本繁重的信息，例如网络上的内容或文本集合中的内容。非结构化信息搜索中的大多数发展都解决了检索数十亿个网页的技术算法；同时，用于Web搜索的接口在同一空间没有进化。要成功使用当前的Web搜索工具，用户通常必须拥有或获取相关文档的作者使用的词汇，并且搜索者不可避免地会遇到信息需求，而这些信息需求无法充分使用一两个票数和广泛的关键字来充分表达，而广泛的关键字通常具有多个含义。这是困扰信息检索系统的词汇不匹配问题，尤其是在搜索陌生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，商业或个人信息收集）和网络搜索之间的差距。它假设搜索者寻求信息以满足他们的需求，而不管信息是结构化的（例如，科学，图书馆或业务信息）还是非结构化的（例如，网络搜索或文本）。例如，结构化信息可以提出新的关键字，以更好地描述用户的需求。该研究计划大写了现有信息组织的投资，以补充非结构化信息检索技术。通过记录测试参与者如何在至少3个月内使用工具，它将确保工具有用并赞赏。已发布的结果将包括开源在线搜索工具原型，这是其他接口设计师和研究人员可以使用的测试引擎，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，凭借其将随着时间的推移设计和测试的新型搜索系统。首先，它将将现有信息组织调查与无处不在的关键字搜索和排名整合在一起，以改善信息发现。例如，用户可以使用一个集成工具，而不是目前必须使用的两个不同工具，可以搜索库目录和Web。其次，随着时间的推移，将对工具进行测试，以确保它们达到搜索者的期望，并且几乎不需要培训。当目标是确保用户能够真正使用并欣赏其最初新颖性的工具时，随着时间的推移，这种类型的测试非常罕见且非常合适。 这项研究旨在支持有兴趣改善信息探索和搜索技术的学生：预算的88％直接向学生（即薪水，旅行费用和计算机）提供。支持的博士学位和硕士学生将成为现有研究小组的一部分，他们将有机会与信息研究学院，麦吉尔和蒙特利尔大学的其他研究小组合作。他们将获得研究，软件设计和开发，测试以及口头/书面交流的技能，这些技能在学术和工业环境中很有价值。总体而言，该研究计划有可能通过建议新的关键字，将相似的信息分组在一起，并拆除有组织的信息收集（例如图书馆目录或商业分类法）和网络搜索之间的人工边界来改善加拿大公民用来搜索各种信息的工具。