04882nam a22005055i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050000900153072001600162072002300178072001500201245019600216250001800412264006900430300006700499336002600566337002600592338003600618347002400654490006200678505058400740520221201324650003203536650002903568650003403597650003203631650002903663650002203692700008103714700007503795700008003870700007403950700007604024710003404100773002604134776003604160776003604196776003604232830006204268856004604330978-3-031-46549-9DE-He21320251030112026.0cr nn 008mamaa240424s2024    sz |    s    |||| 0|eng d  a97830314654997 a10.1007/978-3-031-46549-92doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema10aArtificial Intelligence and Visualization: Advancing Visual Knowledge Discoveryh[electronic resource] /cedited by Boris Kovalerchuk, Kawa Nazemi, Răzvan Andonie, Nuno Datia, Ebad Banissi.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXXI, 503 p. 280 illus., 258 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aStudies in Computational Intelligence,x1860-9503 ;v11260 aVisualizing the Unseen: Unleashing Knowledge Discovery with Lossless Visualizations -- Interactive Decision Tree Creation and Enhancement with Complete Visualization for Explainable Modeling -- Full High-dimensional Intelligible Learning In 2-D Lossless Visualization Space -- Explainable Machine Learning for Categorical and Mixed Data with Lossless Visualization -- Parallel Coordinates for Discovery of Interpretable Machine Learning Models -- Visual Knowledge Discovery with General Line Coordinates -- Unveiling Insights: Empowering AI/ML through Visual Knowledge Discovery.  aThis book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens. . 0aComputational intelligence. 0aArtificial intelligence. 0aEngineeringxData processing.14aComputational Intelligence.24aArtificial Intelligence.24aData Engineering.1 aKovalerchuk, Boris.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aNazemi, Kawa.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aAndonie, Răzvan.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aDatia, Nuno.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aBanissi, Ebad.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303146548208iPrinted edition:z978303146550508iPrinted edition:z9783031465512 0aStudies in Computational Intelligence,x1860-9503 ;v112640uhttps://doi.org/10.1007/978-3-031-46549-9