Chart Question Answering: State of the Art and Future Directions

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dc.contributor.authorHoque, Enamulen_US
dc.contributor.authorKavehzadeh, Parsaen_US
dc.contributor.authorMasry, Ahmeden_US
dc.contributor.editorBruckner, Stefanen_US
dc.contributor.editorTurkay, Cagatayen_US
dc.contributor.editorVrotsou, Katerinaen_US
dc.date.accessioned2022-06-03T05:34:26Z
dc.date.available2022-06-03T05:34:26Z
dc.date.issued2022
dc.description.abstractInformation visualizations such as bar charts and line charts are very common for analyzing data and discovering critical insights. Often people analyze charts to answer questions that they have in mind. Answering such questions can be challenging as they often require a significant amount of perceptual and cognitive effort. Chart Question Answering (CQA) systems typically take a chart and a natural language question as input and automatically generate the answer to facilitate visual data analysis. Over the last few years, there has been a growing body of literature on the task of CQA. In this survey, we systematically review the current state-of-the-art research focusing on the problem of chart question answering. We provide a taxonomy by identifying several important dimensions of the problem domain including possible inputs and outputs of the task and discuss the advantages and limitations of proposed solutions. We then summarize various evaluation techniques used in the surveyed papers. Finally, we outline the open challenges and future research opportunities related to chart question answering.en_US
dc.description.documenttypestar
dc.description.number3
dc.description.sectionheadersMultiple Modalities and Mediums
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14573
dc.identifier.issn1467-8659
dc.identifier.pages555-572
dc.identifier.pages18 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14573
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14573
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing --> Visualization; Computing methodologies --> Natural language processing
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectComputing methodologies
dc.subjectNatural language processing
dc.titleChart Question Answering: State of the Art and Future Directionsen_US
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