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Author: Sergey Kitaev
Publisher: Springer
ISBN: 3319258591
Category : Computers
Languages : en
Pages : 264
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Book Description
This is the first comprehensive introduction to the theory of word-representable graphs, a generalization of several classical classes of graphs, and a new topic in discrete mathematics. After extensive introductory chapters that explain the context and consolidate the state of the art in this field, including a chapter on hereditary classes of graphs, the authors suggest a variety of problems and directions for further research, and they discuss interrelations of words and graphs in the literature by means other than word-representability. The book is self-contained, and is suitable for both reference and learning, with many chapters containing exercises and solutions to seleced problems. It will be valuable for researchers and graduate and advanced undergraduate students in discrete mathematics and theoretical computer science, in particular those engaged with graph theory and combinatorics, and also for specialists in algebra.
Author: Sergey Kitaev
Publisher: Springer
ISBN: 3319258591
Category : Computers
Languages : en
Pages : 264
Get Book
Book Description
This is the first comprehensive introduction to the theory of word-representable graphs, a generalization of several classical classes of graphs, and a new topic in discrete mathematics. After extensive introductory chapters that explain the context and consolidate the state of the art in this field, including a chapter on hereditary classes of graphs, the authors suggest a variety of problems and directions for further research, and they discuss interrelations of words and graphs in the literature by means other than word-representability. The book is self-contained, and is suitable for both reference and learning, with many chapters containing exercises and solutions to seleced problems. It will be valuable for researchers and graduate and advanced undergraduate students in discrete mathematics and theoretical computer science, in particular those engaged with graph theory and combinatorics, and also for specialists in algebra.
Author: Jason Oberholtzer
Publisher: Sourcebooks, Inc.
ISBN: 1402267401
Category : Humor
Languages : en
Pages : 209
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Book Description
Ever shared, laughed at, cried over, or thrown darts at a chart? Have you ever put together a report and thought, gee, I could use a chart here. Then I Love Charts: The Book is the perfect addition to your collection. Based on the highly successful humor blog, this compilation includes the best never-before-seen charts. The book ranges across many subjects from the absurd and ironic to the starkly literal, with charts dedicated to love, the minutiae of every day life, and pop culture, as well as charts about politics, technology, and social issues.
Author: Robert Mercaş
Publisher: Springer Nature
ISBN: 3030287963
Category : Mathematics
Languages : en
Pages : 340
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Book Description
This book constitutes the refereed proceedings of the 12th International Conference on Combinatorics on Words, WORDS 2019, held in Loughborough, UK, in September 2019. The 21 revised full papers presented in this book together with 5 invited talks were carefully reviewed and selected from 34 submissions. WORDS is the main conference series devoted to the mathematical theory of words. In particular, the combinatorial, algebraic and algorithmic aspects of words are emphasized. Motivations may also come from other domains such as theoretical computer science, bioinformatics, digital geometry, symbolic dynamics, numeration systems, text processing, number theory, etc.
Author: Andreas Brieden
Publisher: Springer Nature
ISBN: 3031468260
Category :
Languages : en
Pages : 204
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Book Description
Author: Julia Silge
Publisher: "O'Reilly Media, Inc."
ISBN: 1491981628
Category : Computers
Languages : en
Pages : 193
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Book Description
Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.
Author: Heiko Paulheim
Publisher: Springer Nature
ISBN: 3031303873
Category : Computers
Languages : en
Pages : 165
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Book Description
This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.
Author: Rajat Kalia
Publisher: Lulu.com
ISBN: 1365766039
Category :
Languages : en
Pages : 76
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Book Description
Author: Cole Nussbaumer Knaflic
Publisher: John Wiley & Sons
ISBN: 1119002265
Category : Mathematics
Languages : en
Pages : 288
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Book Description
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Author:
Publisher: SIAM
ISBN: 9780898713138
Category : Mathematics
Languages : en
Pages : 532
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Book Description
Annotation Proceedings of a conference that took place in Austin, Texas in January 1993. Contributors are impressive names from the field of computer science, including Donald Knuth, author of several computer books of "biblical" importance. The diverse selection of paper topics includes dynamic point location, ray shooting, and the shortest paths in planar maps; optimistic sorting and information theoretic complexity; and an optimal randomized algorithm for the cow-path problem. No index. Annotation copyright by Book News, Inc., Portland, OR.
Author: I. Tiddi
Publisher: IOS Press
ISBN: 1643680811
Category : Computers
Languages : en
Pages : 314
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Book Description
The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
