Search and information retrieval systems are becoming more expressive in interpreting user queries beyond the traditional weighted bag-of-words model of document retrieval. For example, searching for a flight status or a game score returns a dynamically generated response along with supporting, pre-authored documents contextually relevant to the query. In this paper, we extend this hybrid search paradigm to data repositories that contain curated data sources and visualization content. We introduce a semantic search interface, OLIO, that provides a hybrid set of results comprising both auto-generated visualization responses and pre-authored charts to blend analytical question-answering with content discovery search goals. We specifically explore three search scenarios - question-and-answering, exploratory search, and design search over data repositories. The interface also provides faceted search support for users to refine and filter the conventional best-first search results based on parameters such as author name, time, and chart type. A preliminary user evaluation of the system demonstrates that OLIO's interface and the hybrid search paradigm collectively afford greater expressivity in how users discover insights and visualization content in data repositories.

翻译：搜索与信息检索系统在解释用户查询方面正日益超越传统文档检索中基于加权词袋模型的表达方式。例如，查询航班状态或比赛得分时，系统不仅返回动态生成的响应结果，还会附带与查询上下文相关的预撰写文档。本文将这一混合搜索范式扩展至包含精选数据源与可视化内容的数据仓库。我们提出名为OLIO的语义搜索接口，该接口通过整合自动生成的可视化响应与预撰写图表，形成包含分析型问答与内容发现搜索目标的混合结果集。我们重点探索了三种搜索场景：数据仓库中的问答式搜索、探索性搜索及设计型搜索。该接口还支持分面搜索功能，允许用户根据作者姓名、时间及图表类型等参数对传统优先进制结果进行精炼与筛选。系统初步用户评估表明，OLIO的接口设计及混合搜索范式共同提升了用户在数据仓库中发现洞见与可视化内容的表达力。