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ABSTRACT We present VisIRR, an interactive visual information retrieval and recommendation system for large-scale document data. ... Starting with a query, VisIRR visualizes the retrieved documents in a scatter plot along with their topic summary. ... The work was supported in part by NSF grant CCF-0808863 and DARPA XDATA grant FA8750-12-2-0309. ...doi:10.1109/vast.2014.7042511 dblp:conf/ieeevast/ChooLKLLKSSDP14 fatcat:aja236wrjfayfkhf57tjrkuuvq
You both made me a better researcher and a better person. I am beyond grateful for the time I spent around you. ... Additionally, I would like to thank Evangelos Milios from the Dalhousie University that participated in this Master's project since day one with many ideas and solutions. ... However, it is not recommended for an extremely large data set. ...doi:10.1145/3342558.3345401 dblp:conf/doceng/DiasMO19 fatcat:i2rzuaixujdcjj3wl7stpmneqq
Abstract-Bibliographic data such as collections of scientific articles and citation networks have been studied extensively in information visualization and visual analytics research. ... A questionnaire study with 14 visual analytics experts confirms that SurVis meets the initially formulated requirements. ... Fabian Beck is indebted to the Baden-Württemberg Stiftung for the financial support of this research project within the Postdoctoral Fellowship for Leading Early Career Researchers. ...doi:10.1109/tvcg.2015.2467757 pmid:26529698 fatcat:na4bhc2imje5xezm2figmzfgwa
Inspired by emerging large-scale visualization collections and the difficulty in finding relevant information, we investigate a content-based approach for visualization recommendation in the VizCommender ... In this dissertation, we demonstrate how a data-driven prototyping process based on real-world data can lead to novel contributions in information visualization with high industry relevance. ... Drake, and H. Park. Visirr: Visual analytics for information retrieval and recommendation with large-scale document data. In IEEE Conf. ...doi:10.14288/1.0401844 fatcat:wftlmm4krbhcvalxou2gchlqaq