Next Generation Information Processing System: Proceedings of Iccet 2020, Volume 2, Deshpande Prachi, Abraham Ajith, Iyer Brijesh
Автор: Rocha Бlvaro, Ferrбs Carlos, Montenegro Marin Carlos Enrique Название: Information Technology and Systems: Proceedings of Icits 2020 ISBN: 303040689X ISBN-13(EAN): 9783030406899 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Review of information systems with technological development for tourism planning with an emphasis on host communities.- A Systematic Review on IoT and E-services Co-Production.- Conceptual Framework for Social Media Usage in Public Services - An Indian Perspective.- Extending Persuasive System Design Frameworks: an Exploratory Study.- A new mathematical model for the vehicle routing problem with backhauls and time windows.- Using Architecture Patterns in the Conceptual Model of an eGov Software.
Описание: This book constitutes the refereed proceedings of the 11th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2020, held in Hangzhou, China, in July 2020. The 24 full papers and 5 short papers presented were carefully reviewed and selected from 36 submissions. and computer vision and image understanding.
Описание: This book constitutes the refereed proceedings of the 27th International Symposium on String Processing and Information Retrieval, SPIRE 2020, held in Orlando, FL, USA, in October 2020. The 17 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 32 submissions. information retrieval;
Автор: Alberto H. F. Laender, Anderson A. Ferreira, Marcos Andre Goncalves Название: Automatic Disambiguation of Author Names in Bibliographic Repositories ISBN: 1681738597 ISBN-13(EAN): 9781681738598 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9979.00 р. Наличие на складе: Нет в наличии.
Описание: This book deals with a hard problem that is inherent to human language: ambiguity.
In particular, we focus on author name ambiguity, a type of ambiguity that exists in digital bibliographic repositories, which occurs when an author publishes works under distinct names or distinct authors publish works under similar names. This problem may be caused by a number of reasons, including the lack of standards and common practices, and the decentralized generation of bibliographic content. As a consequence, the quality of the main services of digital bibliographic repositories such as search, browsing, and recommendation may be severely affected by author name ambiguity. The focal point of the book is on automatic methods, since manual solutions do not scale to the size of the current repositories or the speed in which they are updated. Accordingly, we provide an ample view on the problem of automatic disambiguation of author names, summarizing the results of more than a decade of research on this topic conducted by our group, which were reported in more than a dozen publications that received over 900 citations so far, according to Google Scholar. We start by discussing its motivational issues (Chapter 1). Next, we formally define the author name disambiguation task (Chapter 2) and use this formalization to provide a brief, taxonomically organized, overview of the literature on the topic (Chapter 3). We then organize, summarize and integrate the efforts of our own group on developing solutions for the problem that have historically produced state-of-the-art (by the time of their proposals) results in terms of the quality of the disambiguation results. Thus, Chapter 4 covers HHC - Heuristic-based Clustering, an author name disambiguation method that is based on two specific real-world assumptions regarding scientific authorship. Then, Chapter 5 describes SAND - Self-training Author Name Disambiguator and Chapter 6 presents two incremental author name disambiguation methods, namely INDi - Incremental Unsupervised Name Disambiguation and INC- Incremental Nearest Cluster. Finally, Chapter 7 provides an overview of recent author name disambiguation methods that address new specific approaches such as graph-based representations, alternative predefined similarity functions, visualization facilities and approaches based on artificial neural networks. The chapters are followed by three appendices that cover, respectively: (i) a pattern matching function for comparing proper names and used by some of the methods addressed in this book; (ii) a tool for generating synthetic collections of citation records for distinct experimental tasks; and (iii) a number of datasets commonly used to evaluate author name disambiguation methods. In summary, the book organizes a large body of knowledge and work in the area of author name disambiguation in the last decade, hoping to consolidate a solid basis for future developments in the field.
Автор: Ferreira Anderson A., Gonзalves Marcos Andrй, Laender Alberto H. F. Название: Automatic Disambiguation of Author Names in Bibliographic Repositories ISBN: 1681738570 ISBN-13(EAN): 9781681738574 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7207.00 р. Наличие на складе: Нет в наличии.
Описание: This book deals with a hard problem that is inherent to human language: ambiguity.
In particular, we focus on author name ambiguity, a type of ambiguity that exists in digital bibliographic repositories, which occurs when an author publishes works under distinct names or distinct authors publish works under similar names. This problem may be caused by a number of reasons, including the lack of standards and common practices, and the decentralized generation of bibliographic content. As a consequence, the quality of the main services of digital bibliographic repositories such as search, browsing, and recommendation may be severely affected by author name ambiguity. The focal point of the book is on automatic methods, since manual solutions do not scale to the size of the current repositories or the speed in which they are updated. Accordingly, we provide an ample view on the problem of automatic disambiguation of author names, summarizing the results of more than a decade of research on this topic conducted by our group, which were reported in more than a dozen publications that received over 900 citations so far, according to Google Scholar. We start by discussing its motivational issues (Chapter 1). Next, we formally define the author name disambiguation task (Chapter 2) and use this formalization to provide a brief, taxonomically organized, overview of the literature on the topic (Chapter 3). We then organize, summarize and integrate the efforts of our own group on developing solutions for the problem that have historically produced state-of-the-art (by the time of their proposals) results in terms of the quality of the disambiguation results. Thus, Chapter 4 covers HHC - Heuristic-based Clustering, an author name disambiguation method that is based on two specific real-world assumptions regarding scientific authorship. Then, Chapter 5 describes SAND - Self-training Author Name Disambiguator and Chapter 6 presents two incremental author name disambiguation methods, namely INDi - Incremental Unsupervised Name Disambiguation and INC- Incremental Nearest Cluster. Finally, Chapter 7 provides an overview of recent author name disambiguation methods that address new specific approaches such as graph-based representations, alternative predefined similarity functions, visualization facilities and approaches based on artificial neural networks. The chapters are followed by three appendices that cover, respectively: (i) a pattern matching function for comparing proper names and used by some of the methods addressed in this book; (ii) a tool for generating synthetic collections of citation records for distinct experimental tasks; and (iii) a number of datasets commonly used to evaluate author name disambiguation methods. In summary, the book organizes a large body of knowledge and work in the area of author name disambiguation in the last decade, hoping to consolidate a solid basis for future developments in the field.
Автор: Ilyas Ihab F., Chu Xu Название: Data Cleaning ISBN: 1450371531 ISBN-13(EAN): 9781450371537 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9023.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions.
Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems.
This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, we give an overview of the end-to-end data cleaning process, describing various error detection and repair methods, and attempt to anchor these proposals with multiple taxonomies and views. Specifically, we cover four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, we include a chapter that specifically explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models.
This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate.
Описание: Introduction.- Formation of Flexible Linguistic Values and Their Mathematical Models ── Formation Principles and Modeling of Imprecise Information.- Fundamental Theories of Flexible Sets and Flexible Linguistic Values ── Mathematical Theories about Imprecise Information.- Truth-Degreed Logic and Flexible-Linguistic-Truth-Valued Logic ── Logic Theories about Imprecise Information.- Approximate Reasoning with Flexible Linguistic Rules and Approximate Evaluation of Flexible Linguistic Functions ── Reasoning and Computation with Imprecise Information and Knowledge.- Imprecise-Problem Solving and Imprecise-Knowledge Discovery──Application of Imprecise-Information Processing.- Quantifiable Rigid Linguistic Values and Information Processing with Degrees ── Extension of Imprecise Information.- Probabilities of Flexible Events, Believability-Degrees of Flexible Propositions and Reasoning with Believability-Degrees as well as Modal Propositions
Описание: This book gathers selected high-quality research papers presented at the Fifth International Congress on Information and Communication Technology, held at Brunel University, London, on February 20-21, 2020.
Описание: This book constitutes the refereed proceedings of the 11th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2020, held in Dortmund, Germany, in February 2020. The 19 revised full papers presented were carefully reviewed and selected from 33 submissions.
Описание: The papers are grouped in topical sections on world wide web, recommendation, query processing and algorithm, natural language processing, machine learning, graph query, edge computing and data mining, data privacy and security, and blockchain.
Clock Synchronization for Mobile Molecular Communication in Nanonetworks.- A Cooperative Molecular Communication for targeted drug Delivery.- Performance of Diffusion-based MIMO Molecular Communications and Dual Threshold Algorithm.- Binary Concentration Shift Keying with Multiple Measurements of Molecule Concentration in Mobile Molecular Communication.- Real-Time Seven Segment Display Detection and Recognition Online System using CNN.- A novel method for extracting high-quality RR intervals from noisy single-lead ECG signals.- Leak-resistant design of DNA strand displacement systems.- Chessboard EEG Images Classification for BCI Systems Using Deep Neural Network.- Causal Network Analysis and Fault Root Point Detection Based on Symbolic Transfer Entropy.- Personalized EEG feature extraction method based on filter bank and elastic network.- Release rate optimization based on M/M/c/c queue in local nanomachine-based targeted drug delivery.- Research on Course Control of Unmanned Surface Vehicle.- Design and Experiment of a Double-layer Vertical Axis Wind Turbine.- Real-Time Obstacle Detection Based on Monocular Vision for Unmanned Surface Vehicles.- A Method of Data Integrity Check and Repair in Big Data Storage Platform.- A Study of Image Recognition for Standard Convolution and Depthwise Separable Convolution.- A Novel Genetic Algorithm-based DES Key Generation Scheme.- Developing an Intelligent Agricultural System based on Long Short-Term Memory.- Detection of atherosclerotic lesions based on molecular Communication.- Design for Detecting Red Blood Cell Deformation at Different Flow Velocities in Blood Vessel.- Intelligent Power Controller of Wireless Body Area Networks based on Deep Reinforcement Learning.- Target Tracking Based on DDPG in Wireless Sensor Network.- A fuzzy tree system based on cuckoo search algorithm for target tracking in Wireless Sensor Network.- Sensor scheme for target tracking in Mobile Sensor Networks.- Molecular MIMO Communications Platform with BTSK for In-Vessel Network Systems.- Preliminary Studies on Flow Assisted Propagation of Fluorescent Microbeads in Microfluidic Channels for Molecular Communication Systems.- Comparative Evaluation of a New Sensor for Superparamagnetic Iron-Oxide Nanoparticles in a Molecular Communication Setting.- Localization of a Passive Molecular Transmitter with a Sensor Network.
Описание: A unified treatment of the latest game theoretic approaches for designing, modeling, and optimizing emerging wireless communication networks. Covering theory, analytical tools, and applications, it is ideal for researchers and graduate students in academia and industry designing efficient, scalable and robust protocols for future wireless networks.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
