Olio: A Semantic Search Interface for Data Repositories

要旨

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.

著者
Vidya Setlur
Tableau Research, Palo Alto, California, United States
Andriy Kanyuka
Tableau, Vancouver, British Columbia, Canada
Arjun Srinivasan
Tableau Research, Seattle, Washington, United States
論文URL

https://doi.org/10.1145/3586183.3606806

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Data Dreamers: Math, Stats and Visualization

Gold Room
6 件の発表
2023-11-01 18:00:00
2023-11-01 19:20:00