CAREER: Making Aggregated Search Results More Effective and Useful

聚合搜索是将来自多个独立搜索引擎的结果组合到单个呈现中的任务。最广泛使用的聚合搜索系统是商业搜索门户，如Google。除了web搜索之外，商业搜索门户还提供对广泛的辅助搜索服务或垂直搜索的访问，其集中于特定类型的媒体（例如，图像、视频）或搜索任务（例如，搜索新闻、本地企业）。 聚合搜索系统负责预测要呈现哪些垂直领域（用户想看图片还是新闻？）以及在哪里/如何展示它们。这个项目将研究一种称为聚合搜索一致性的现象及其对搜索行为的影响。给定一个模糊的查询（例如，“Saturn”），搜索引擎的常见策略是使其结果多样化（例如，返回关于汽车和行星的结果）。 聚合搜索一致性是来自不同来源的结果集中在查询的相似意义上的程度。该项目的成果将提供所需的知识，以扩大在广泛领域的搜索的可及性。所产生的测试集合将允许其他人复制这项工作的结果并测试他们自己的解决方案。该软件将使其他人能够对搜索行为进行大规模的远程研究。从用户研究中获得的见解将对心理学和营销等其他领域的研究人员感兴趣。PI之前的研究发现，垂直结果中的查询感觉会影响用户与聚合结果页面上其他组件的交互，即所谓的“溢出”效应。这个项目将研究聚合搜索一致性如何影响搜索行为，并将这些知识纳入聚合搜索评估和预测的新方法中。具体而言，将实现四个目标。(1)将进行一系列的用户研究，以调查用户的不同因素，搜索任务，结果呈现和布局如何确定从一个组件到另一个组件的溢出水平。(2)利用从这些研究中获得的见解，一个新的测试收集评估方法将开发和验证模型的跨组件的影响。(3)由于现有系统的流水线架构，来自不同组件的结果彼此完全独立。将开发和评估新的算法，以预测每个组件的哪些结果要显示以及如何显示。目标是尽量减少负面的跨部门影响。(4)这些方法的普遍性将在另外两个领域进行测试：图书馆搜索和新闻报道聚合。聚合搜索有助于对不同类型的媒体进行单一查询访问，这需要定制的搜索解决方案。它是商业搜索门户背后的底层技术，也广泛用于图书馆、移动的和桌面搜索等其他领域。该项目将研究一种目前尚未得到充分理解的现象，也没有在现有的评估方法和聚合搜索的算法解决方案中得到解决。

Aggregated search is the task of combining results from multiple independent search engines into a single presentation. The most widely used aggregated search systems are commercial search portals such as Google. In addition to web search, commercial search portals provide access to a wide range of auxiliary search services, or verticals, that focus on a specific type of media (e.g., images, videos) or search task (e.g., search for news, local businesses). Aggregated search systems are responsible for predicting which verticals to present (Does the user want to see images or news?) and where/how to present them. This project will study a phenomenon called aggregated search coherence and its effect on search behavior. Given an ambiguous query (e.g., "saturn"), a common strategy for a search engine is to diversify its results (e.g., to return results about the car and the planet). Aggregated search coherence is the extent to which results from different sources focus on similar senses of the query. The outcomes of this project will provide the knowledge required to expand the accessibility of search across a wide range of domains. The test collection produced will allow others to reproduce the results of this work and test their own solutions. The software will enable others to perform large-scale remote studies of search behavior. Insights gained from the user studies will be of interest to researchers in other fields such as psychology and marketing.Prior research by the PI found that the query-senses in the vertical results can affect user interaction with other components on the aggregated results page, the so-called "spill-over" effect. This project will investigate how aggregated search coherence affects search behavior and will incorporate this knowledge into new methods for aggregated search evaluation and prediction. Specifically, four objectives will be tackled. (1) A series of user studies will be conducted to investigate how different factors of the user, the search task, the results presentation, and the layout determine the level of spill-over from one component to another. (2) Using the insights gained from these studies, a new test-collection evaluation methodology will be developed and validated that models cross-component effects. (3) Due to the pipeline architecture of existing systems, results from different components are completely independent of each other. New algorithms will be developed and evaluated for predicting which results from each component to display and how. The goal will be to minimize negative cross-component effects. (4) The generalizability of the methods will be tested on two additional domains: library search and news story aggregation. Aggregated search facilitates single-query access to different types of media, which require customized search solutions. It is the underlying technology behind commercial search portals and also widely used in other domains such as library, mobile, and desktop search. The project will study a phenomenon that is not currently well-understood, nor addressed in existing evaluation methods and algorithmic solutions for aggregated search.