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Author: National Aeronautics and Space Adm Nasa Publisher: ISBN: 9781729062975 Category : Languages : en Pages : 34
Book Description
This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes. Stewart, Mark E. M. Glenn Research Center NAS3-27816; RTOP 509-10-11...
Author: National Aeronautics and Space Adm Nasa Publisher: ISBN: 9781729062975 Category : Languages : en Pages : 34
Book Description
This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes. Stewart, Mark E. M. Glenn Research Center NAS3-27816; RTOP 509-10-11...
Author: National Aeronautics and Space Administration (NASA) Publisher: Createspace Independent Publishing Platform ISBN: 9781721227143 Category : Languages : en Pages : 26
Book Description
This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes. Stewart, Mark Glenn Research Center NASA/CR-2000-209947, E-12194, NAS 1.26:209947
Author: Elad Segev Publisher: Routledge ISBN: 1000471918 Category : Psychology Languages : en Pages : 223
Book Description
Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.
Author: Rayner Alfred Publisher: Springer Nature ISBN: 9811685150 Category : Technology & Engineering Languages : en Pages : 887
Book Description
This book gathers the proceedings of the Seventh International Conference on Computational Science and Technology (ICCST 2021), held in Labuan, Malaysia, on 28–29 August 2021. The respective contributions offer practitioners and researchers a range of new computational techniques and solutions, identify emerging issues, and outline future research directions, while also showing them how to apply the latest large-scale, high-performance computational methods.
Author: Dipanjan Sarkar Publisher: Apress ISBN: 1484243544 Category : Computers Languages : en Pages : 688
Book Description
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Author: Phillip C.-Y. Sheu Publisher: John Wiley & Sons ISBN: 0470920874 Category : Computers Languages : en Pages : 408
Book Description
Presents the state of the technology and points to future directions for semantic computing Semantic computing, a rapidly evolving interdisciplinary field, seeks to structure, design, and manipulate computer content to better satisfy the needs and intentions of users and create a more meaningful user experience. This remarkable contributed work examines the art, engineering, technology, and applications of the field. Moreover, it brings together researchers from such disciplines as natural language processing, software engineering, multimedia semantics, semantic Web, signal processing, and pattern recognition in order to provide a single source that presents the state of the technology and points to new breakthroughs on the horizon. Semantic Computing begins with an introduction that explores the concepts, technology, applications, and future of semantic computing. Next, the book is divided into four parts: Part One: Semantic Analysis Part Two: Semantic Languages and Integration Part Three: Semantic Applications Part Four: Semantic Programming and Interface As readers progress through the book, they,ll learn not only the underlying science, but also the fundamental technological building blocks of semantic computing. Moreover, they,ll discover a variety of cross-disciplinary solutions to current computing and communication problems. Throughout the book, references to the primary literature enable further investigation of each individual topic. Semantic Computing is ideal for industrial managers, researchers, and engineers seeking to design the next generation of computing systems in order to better meet user needs. It is also recommended as a textbook for senior undergraduate and graduate-level semantic computing courses.
Author: National Aeronautics and Space Adm Nasa
Author: National Aeronautics and Space Adm Nasa
Author: Mark E. M. Stewart
Author: National Aeronautics and Space Administration (NASA)
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Author: 
Author: Elad Segev
Author: 
Author: Rayner Alfred
Author: Dipanjan Sarkar
Author: Phillip C.-Y. Sheu