الصفحة 3
الصفحة 3
Grammatical Inference : Algorithms and Applications ; 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006, Proceedings
The topics discussed range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to applications to natural language processing.
Geographic Information Science ; 5th International Conference, GIScience 2008, Park City, UT, USA, September 23-26, 2008. Proceedings
This book constitutes the refereed proceedings of the 5th International Conference on Geographic Information Secience, GIScience 2008, held in Park City, UT, USA, in September 2008.The 24 revised full papers presented were carefully reviewed and selected from 77 submissions. Among the traditional topics addressed are spatial relations, geographic dynamics, and spatial data types. A significant number of papers deal with navigation networks, location-based services, and spatial information query and retrieval. Geo-sensors, mobile computing, and Web mapping rank among the important new directions.
Fundamentals of Artificial Intelligence
Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Fundamental approaches to software engineering ; 24th International Conference, FASE 2021, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021, Luxembourg City, Luxembourg, March 27 – April 1, 2021, Proceedings
This book constitutes the proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering, FASE 2021, which took place during March 27–April 1, 2021, and was held as part of the Joint Conferences on Theory and Practice of Software, ETAPS 2021.
From Opinion Mining to Financial Argument Mining
Financial opinion mining is a branch of traditional opinion mining and sentiment analysis which shares the basic notions of traditional approaches and adds its own domain-specific characteristics. In Sect. 1.1, we start with a common definition of general opinion mining after which we briefly overview traditional research directions.
From Data to Models and Back ; 9th International Symposium, DataMod 2020, Virtual Event, October 20, 2020, Revised Selected Papers
This book constitutes the refereed proceedings of the 9th International Symposium on From Data Models and Back, DataMod 2020, held virtually, in October 2020. The 11 full papers and 3 short papers presented in this book were selected from 19 submissions. The papers are grouped in these topical sections: machine learning; simulation-based approaches, and data mining and processing related approaches.
Foundations of software science and computation structures ; 24th International conference, FOSSACS 2021, Held as Part of the European joint conferences on theory and practice of software, ETAPS 2021, Luxembourg City, Luxembourg, March 27 – April 1, 2021, proceedings
This book constitutes the proceedings of the 24th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2021, which was held during March 27 until April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic.
Foundation models for natural language processing : pre-trained language models integrating media
Covers basic natural language processing models, pre-trained language models BERT, GPT, and sequence-to-sequence converters, as well as the concepts of self-attention and context-sensitive embedding. Various approaches to improving these models are then discussed, such as expanding the pre-training parameters, increasing the length of input texts, or incorporating additional knowledge. An overview of the best performing models is then provided for about twenty application areas, e.g., question answering, translation, story generation, dialogue systems, image generation from text, etc. For each application area, the strengths and weaknesses of existing models are discussed, and an overview of further developments is provided. In addition, links to freely available code are provided. The concluding chapter summarizes the economic opportunities, risk mitigation, and potential developments of AI.
Finite-state methods and natural language processing ; 5th International Workshop, FSMNLP 2005, Helsinki, Finland, September 1-2, 2005, Revised Papers
This book constitutes the thoroughly refereed post-proceedings of the 5th International Workshop on Finite-State Methods in Natural Language Processing, FSMNLP 2005, held in Helsinki, Finland, September 2005. The book presents 24 revised full papers and seven revised poster papers together with two invited contributions and abstracts of six software demos. Topics include morphology, optimality theory, some special FSM families, weighted FSM algorithms, FSM representations, exploration, ordered structures, and surface parsing.
Explainable AI with Python
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others.
Evaluation of text summaries based on linear optimization of content metrics
Covers both theoretical contributions and practical applications in security system design by applying the Internet of Things (IoT) and CI. It further explains the application of IoT in the design of modern security systems and how IoT blended with computational intel- ligence can make any security system improved and realizable. Key features: Focuses on the computational intelligence techniques of security system design Covers applications and algorithms of discussed computational intelligence techniques Includes convergence-based and enterprise integrated security systems with their applications Explains emerging laws, policies, and tools affecting the landscape of cyber security Discusses application of sensors toward the design of security systems This book will be useful for graduate students and researchers in electrical, computer engineering, security system design and engineering
English proofreader
Using Natural Language Processing via Deep Learning, we will attempt to implement a context-sensitive spelling error correction system focused on casual text messaging. For example, usual autocorrect systems will not correct a sentence like “An apple is better than a banana” as this is a syntactically correct sentence. However, a correction should be made here to the word “then” and the sentence should be, “An apple is better than a banana.” These types of mistakes are common in people texting and can be found for example in people learning English as a second language. Natural Language Processing can be summarized as combining the utilization of computation to understand the concepts of natural language and speech.
Emergence of Communication and Language
This volume brings together studies from diverse disciplines, showing how they can inform and stimulate each other. It includes work in linguistics, psychology, neuroscience, anthropology and computer science. New empirical work is reported on both human and animal communication, using some novel techniques that have only recently become viable. A principal theme is the importance of studies involving artificial agents, their contribution to the body of knowledge on the emergence of communication and language, and the role of simulations in exploring some of the most significant issues. A number of different synthetic systems are described, demonstrating how communication can emerge in natural and artificial organisms. Theories on the origins of language are supported by computational and robotic experiments. Worldwide contributors to this volume include some of the most influential figures in the field, delivering essential reading for researchers and graduates in the area, as well as providing fascinating insights for a wider readership.
Drousi: A private lessons management system
Private teaching is considered to be an effective way to increase academic achievement of students and it seen as being a supplementary education, so it has become very common all around the world, however, previous studies have come to different conclusions regarding its necessity, so Drousi application had been made ,it’s a user-friendly mobile application to manage and arrange private lessons, and There has never been a better time to become a private tutor, as class sizes in schools increase, this can result in teachers being unable to give their undivided attention to students, and this document lays out a project plan for the development of “Drousi”, The plan will include a summary of the system functionality and how it implemented.
Deep Learning with PyTorch Lightning : Build and train high-performance artificial intelligence and self-supervised models using Python
You’ll learn how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. You’ll build a neural network architecture, deploy an application from scratch, and see how you can expand it based on your specific needs, beyond what the framework can provide. In the later chapters, you’ll also learn how to implement capabilities to build and train various models like Convolutional Neural Nets (CNN), Natural Language Processing (NLP), Time Series, Self-Supervised Learning, Semi-Supervised Learning, Generative Adversarial Network (GAN) using PyTorch Lightning.
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
Data science for economics and finance : Methodologies and applications
The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
Data science ; 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part II
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
Data Science ; 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part I
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
