Enabling Integrated Information Access and Retrieval

使人们能够获得信息仍然是一项复杂而具有挑战性的任务，商业网络搜索引擎的巨大成功将用户的期望提高到了非常高的水平。将这种成功转化到Web搜索之外的领域，同时满足这些用户的期望，这是我工作的中心目标。从广义上讲，我的研究兴趣包括信息检索领域内的一系列相互关联的主题，包括搜索接口，评估，索引，排名和文本数据挖掘。我的工作主要是应用性质的，通过实施，实验和性能测量验证的结果。 在这个应用程序下提出的活动建立在我目前的研究基础上，特别是我在索引，排名和建模用户行为方面的工作。在接下来的五年里，我计划将这项工作扩展到有效的多阶段排名，集中检索，高召回检索和搜索会话等主题。此外，我计划解决特定领域的问题，例如城市搜索。 我的研究在几个层面上都有潜在的影响力。对高效索引和排序的基础研究可以提高系统性能，降低对机器和功率的要求，这对于运行数千台机器的系统非常重要。集中检索的新方法将有助于在复杂的书籍、期刊和其他文件集合中获取信息，帮助科学和其他领域的研究人员。最大化召回的搜索技术（即，所发现的相关材料的量），同时最小化人工努力，在需要近乎详尽的结果的受体领域中具有应用。 用于解释和建模搜索会话的方法，特别是根据个性化和上下文，可以直接转化为改进的搜索体验。最后，兴趣点推荐和城市搜索的方法有可能通过生活实验室的基础设施访问开放数据和共享经验。 为了转让技术，我与行业密切合作，包括主要的商业搜索公司、软件顾问以及一些位于滑铁卢的当地初创企业。我的毕业生已经在加拿大和国际上的工业和学术界的机会，包括至少一个加拿大初创企业的成立。 我还经常与软件行业之外的接收者互动，他们涉及许多领域的信息访问问题。 我打算在这个发现补助金的生命周期内保持这种合作方式，并继续强调研究生研究活动和行业之间的联系。

Enabling access to information remains a complex and challenging task, and the tremendous success of commercial Web search engines has raised user expectations to extraordinarily high levels. Translating this success to domains beyond Web search, while matching these user expectations, forms a central goal of my work. Broadly, my research interests encompass a range of interrelated topics within the field of information retrieval, including search interfaces, evaluation, indexing, ranking, and text data mining. My work is primarily of an applied nature, with the results validated through implementation, experimentation, and performance measurement. The activities proposed under this application build upon my current research, particularly my work on indexing, ranking, and modeling user behaviour. Over the next five years, I plan to extend this work to topics such as efficient multi-staged ranking, focused retrieval, high-recall retrieval, and search sessions. In addition, I plan to address problems in specific domains, such as city search. My research has potential for impact at several levels. Basic research on efficient indexing and ranking can increase system performance, reducing requirements for machines and power, which is important for systems operating over thousands of machines. New methods for focused retrieval would facilitate information access across complex collections of books, journals and other documents, helping researchers in science and other areas. Search technology to maximize recall (i.e., the amount of relevant material found) while minimizing human effort has application in receptor domains where near-exhaustive results are required.  Methods for interpreting and modeling search sessions, particularly in the light of personalization and context, can directly translate to improved searcher experience. Finally, methods for point-of-interest recommendation and city search have the potential to enable access to open data and shared experience through the infrastructure of a living lab. To transfer technology, I work closely with industry, including major commercial search companies, software consultants, as well as a number of local Waterloo-based start-ups. My graduating students have gone on to opportunities in industry and academia, both within Canada and internationally, including the founding of a least one Canadian start-up.  I also regularly interact with receptors outside the software industry who are involved in information access problems across many domains.  I intend to maintain this collaborative approach over the lifetime of this Discovery Grant, with a continuing emphasis on links between graduate student research activities and industry.