Focused on Cognitive Tasks Interactive Search Interface

Golitsyna, O. L.; Maksimov, N. V.; Monankov, K. V.

doi:10.1016/j.procs.2018.11.078

Cited by 2 publications

(2 citation statements)

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“…Exclusions were made if the papers (1) presented deeply domain-specific user, task, or interface requirements which would not hold as generalized information-seeking processes (e.g., domain-specific datasets, AR, VR, mobile-exclusive, etc. ); (2) described ontology integrations that are not user-facing (e.g., system-facing integration); (3) involved ontology integrations for tasks not related to the information-seeking process; (4) concerned systemfacing issues, such as computational search, machine learning algorithms, indexing, storage, networking, and the like, rather than user-facing information search or triage processes; or (5) were not in English.…”

Section: Inclusion and Exclusion Criteriamentioning

confidence: 99%

“…It is both data-driven and user-driven and requires re-computation when users manipulate the information through the visual interface [2,3]. Visual analytics tools (VATs) help users form valuable connections with their information and be more active participants in the analysis process [4,5]. They can be used to support a wide variety of domain tasks, such as making sense of misinformation, searching large document sets, and making decisions regarding health data, to name a few [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach

Demelo

Sedig

2021

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We investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets. The goal is to distill a set of criteria that can help guide the design of such systems. We begin with a background of information search, triage, machine learning, and ontologies. We review research on the multi-stage information-seeking process to distill the criteria. To demonstrate their utility, we apply the criteria to the design of a prototype visual analytics interface: VisualQUEST (Visual interface for QUEry, Search, and Triage). VisualQUEST allows users to plug-and-play document sets and expert-defined ontology files within a domain-independent environment for multi-stage information search and triage tasks. We describe VisualQUEST through a functional workflow and culminate with a discussion of ongoing formative evaluations, limitations, future work, and summary.

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Section: Inclusion and Exclusion Criteriamentioning

confidence: 99%