III: Small: Improving Information Retrieval by Analysis of Temporal Evidence in a Unified Model

信息检索（IR）系统具有固有的时效性。随着时间的推移，文档会发生变化，索引会获取新文档，系统会以不同的方式回答或“字段”查询。这个项目的愿景是利用这种时间性来改进用于预测文档相关性的模型。该方法基于一种新颖的概率框架，允许时间因素提高红外有效性。该框架将时间性作为预测文档相关性的关键因素。最初的工作重点是建立文本检索设置，估计文档与关键字查询的相关性。然而，诸如社交媒体和志愿者维护的知识库等新兴领域具有固有的暂时性，需要新的模型。因此，在项目中，研究的重点是过滤和主题演化问题。本项目开发的方法将使用标准数据集进行实验评估。该项目的预期结果包括用于检索、过滤和组织随时间增量到达的文本数据的改进模型和算法。该项目将在两个方面造福社会。红外系统在人类中发挥着关键作用？S日常信息使用。这个项目将提高公众处理日益复杂的信息环境的能力，因为预期的结果将改进搜索引擎技术。研究成果将主要通过学术会议和期刊传播。工作还将储存在一个档案机构储存库中，使公众能够长期获得成果。有关该项目的进展和一般信息将在该项目的网站（http://timer.lis.illinois.edu）上公布。该项目将为学生提供研究经验，并将促进科学教育。此外，还将开发课程材料，以支持对非技术学生进行信息检索的在线教学。

Information retrieval (IR) systems are inherently temporal. Documents change, indexes acquire new documents, and systems answer or "field" queries differently over time. The vision of this project is to capitalize on this temporality to improve the models used for predicting document relevance. The approach is based on a novel probabilistic framework to allow temporal factors to improve IR effectiveness. The framework situates temporality as a key factor in predicting the document relevance. Initial work focuses on established text retrieval settings, estimating document relevance to keyword queries. However, emerging domains such as social media and volunteer-maintained knowledge bases have an inherent temporality that demands new models. Thus, during the project, research pursues problems of filtering and topic evolution. Methods developed in this project will be experimentally evaluated using standard datasets. The project's expected outcome includes improved models and algorithms for retrieving, filtering, and organizing textual data that arrives incrementally over time. The project will benefit society in two ways. IR systems play a key role in people?s daily information use. This project will advance the public's ability to negotiate an increasingly complex information landscape, because the expected outcomes will improve search engine technology. Research results will be disseminated primarily via academic conferences and journals. Work will also be stored in an archival institutional repository, affording the public long-term access to results. Progress and general information about the project will be published on the project Web site (http://timer.lis.illinois.edu). The project will provide research experience for students and will advance scientific education. In addition, course materials will be developed to support on-line teaching of information retrieval to non-technical students.