EBIMCS '22
| Author | : Rita Yi Man Li |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2022 |
| Genre | : Computer science |
| ISBN | : |
Ebimcs 22
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Intelligent Systems
| Author | : André Britto |
| Publisher | : Springer Nature |
| Total Pages | : 649 |
| Release | : 2021-11-27 |
| Genre | : Computers |
| ISBN | : 3030916995 |
The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in São Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.
Congress on Intelligent Systems
| Author | : Mukesh Saraswat |
| Publisher | : Springer Nature |
| Total Pages | : 933 |
| Release | : 2022-07-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9811694168 |
This book is a collection of selected papers presented at the Second Congress on Intelligent Systems (CIS 2021), organized by Soft Computing Research Society and CHRIST (Deemed to be University), Bengaluru, India, during September 4 – 5, 2021. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as Internet of things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human–computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.
Financial Development and Economic Growth in Malaysia
| Author | : James B. Ang |
| Publisher | : Routledge |
| Total Pages | : 214 |
| Release | : 2008-11-25 |
| Genre | : Business & Economics |
| ISBN | : 113403511X |
This book sheds new light on the evolutionary role of financial system and the interacting mechanisms between financial development and economic growth in the context of Malaysia.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases
| Author | : Michael Kamp |
| Publisher | : Springer Nature |
| Total Pages | : 601 |
| Release | : 2022-02-18 |
| Genre | : Computers |
| ISBN | : 303093733X |
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops:Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021)Workshop on Parallel, Distributed and Federated Learning (PDFL 2021)Workshop on Graph Embedding and Mining (GEM 2021)Workshop on Machine Learning for Irregular Time-series (ML4ITS 2021)Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM 2021)Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2021)Workshop on Bias and Fairness in AI (BIAS 2021)Workshop on Workshop on Active Inference (IWAI 2021)Workshop on Machine Learning for Cybersecurity (MLCS 2021)Workshop on Machine Learning in Software Engineering (MLiSE 2021)Workshop on MIning Data for financial applications (MIDAS 2021)Sixth Workshop on Data Science for Social Good (SoGood 2021)Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2021)Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020)Workshop on Machine Learning for Buildings Energy Management (MLBEM 2021)
Neutrosophic Association Rule Mining Algorithm for Big Data Analysis
| Author | : Mohamed Abdel-Basset |
| Publisher | : Infinite Study |
| Total Pages | : 19 |
| Release | : |
| Genre | : |
| ISBN | : |
Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets.
Data Cleaning
| Author | : Ihab F. Ilyas |
| Publisher | : Morgan & Claypool |
| Total Pages | : 282 |
| Release | : 2019-06-18 |
| Genre | : Computers |
| ISBN | : 1450371558 |
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.
Computer Security -- ESORICS 2019
| Author | : Kazue Sako (Innovation Producer) |
| Publisher | : |
| Total Pages | : 811 |
| Release | : 2019 |
| Genre | : Computer networks |
| ISBN | : 9783030299606 |
The two volume set, LNCS 11735 and 11736, constitutes the proceedings of the 24th European Symposium on Research in Computer Security, ESORIC 2019, held in Luxembourg, in September 2019. The total of 67 full papers included in these proceedings was carefully reviewed and selected from 344 submissions. The papers were organized in topical sections named as follows: Part I: machine learning; information leakage; signatures and re-encryption; side channels; formal modelling and verification; attacks; secure protocols; useful tools; blockchain and smart contracts. Part II: software security; cryptographic protocols; security models; searchable encryption; privacy; key exchange protocols; and web security. --
Communication Strategies
| Author | : Gabriele Kasper |
| Publisher | : Routledge |
| Total Pages | : 234 |
| Release | : 2014-06-03 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 1317894618 |
This book examines the topic of communication strategies, the ways in which people seek to express themselves or understand what someone else is saying or writing. Typically, the term has referred to the strategies that non-native speakers use to address the linguistic and pragmatic problems encountered in interactions with native and non-native speakers of the language in question. Studies adopting a psycholinguistic perspective are well represented and updated in this volume. Other chapters re-examine communication strategies from a sociolinguistic perspective, exploring the strategies non-native speakers and their conversational partners use to create shared meanings in ongoing discourse. These studies reveal how communication strategies can serve to construct participants' identities and social relationships. Finally, the book incorporates a number of chapters which cover strategy-like behaviour in other related areas, such as language pathology, child bilingualism, normal native adult interaction, and mother tongue education. These studies add fresh dimensions to the study of communication strategies, showing how the concept can usefully be extended beyond the realm of second language acquisition and use, and pointing out the commonalities in many domains of language behaviour.
Matrix Methods in Data Mining and Pattern Recognition
| Author | : Lars Elden |
| Publisher | : SIAM |
| Total Pages | : 226 |
| Release | : 2007-07-12 |
| Genre | : Computers |
| ISBN | : 0898716268 |
Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application.Matrix Methods in Data Mining and Pattern Recognition is divided into three parts. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB®. Some mathematical proofs that emphasize the existence and properties of the matrix decompositions are included. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed by the author are: classification of handwritten digits, text mining, text summarization, pagerank computations related to the GoogleÔ search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.Audience The book is intended for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.Contents Preface; Part I: Linear Algebra Concepts and Matrix Decompositions. Chapter 1: Vectors and Matrices in Data Mining and Pattern Recognition; Chapter 2: Vectors and Matrices; Chapter 3: Linear Systems and Least Squares; Chapter 4: Orthogonality; Chapter 5: QR Decomposition; Chapter 6: Singular Value Decomposition; Chapter 7: Reduced-Rank Least Squares Models; Chapter 8: Tensor Decomposition; Chapter 9: Clustering and Nonnegative Matrix Factorization; Part II: Data Mining Applications. Chapter 10: Classification of Handwritten Digits; Chapter 11: Text Mining; Chapter 12: Page Ranking for a Web Search Engine; Chapter 13: Automatic Key Word and Key Sentence Extraction; Chapter 14: Face Recognition Using Tensor SVD. Part III: Computing the Matrix Decompositions. Chapter 15: Computing Eigenvalues and Singular Values; Bibliography; Index.
