Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery

Boris Kovalerchuk · Kawa Nazemi · Răzvan Andonie · Nuno Datia · Ebad Banissi

apr. 2024 · Studies in Computational Intelligence Bók 1126 · Springer Nature

Rafbók

503

Síður

Einkunnir og umsagnir eru ekki staðfestar Nánar

Um þessa rafbók

This 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.

Gefa þessari rafbók einkunn.

Segðu okkur hvað þér finnst.

Upplýsingar um lestur

Snjallsímar og spjaldtölvur

Settu upp forritið Google Play Books fyrir Android og iPad/iPhone. Það samstillist sjálfkrafa við reikninginn þinn og gerir þér kleift að lesa með eða án nettengingar hvar sem þú ert.

Fartölvur og tölvur

Hægt er að hlusta á hljóðbækur sem keyptar eru í Google Play í vafranum í tölvunni.

Lesbretti og önnur tæki

Til að lesa af lesbrettum eins og Kobo-lesbrettum þarftu að hlaða niður skrá og flytja hana yfir í tækið þitt. Fylgdu nákvæmum leiðbeiningum hjálparmiðstöðvar til að flytja skrár yfir í studd lesbretti.

Tilkynna ólöglegt efni