Bio Inspired Algorithms For Data Streaming And Visualization Big Data Management And Fog Computing
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Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing
This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.
Intelligent Information and Database Systems
This two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.
Business Intelligence: An overview
Author: Vinaitheerthan Renganathan
language: en
Publisher: Vinaitheerthan Renganathan
Release Date: 2021-03-18
Business organizations develop strategies and set targets which focus on maximizing profit, reduce cost, improving customer satisfaction & retention and operational performance. In order to achieve the set targets, organizations need to continuously monitor status of organizational performance. Organizations need to collect, store, organize, transform the data to know the current status of set targets. Business Intelligence tools help the organizations to draw meaningful and actionable insights from the raw data in achieving the set targets. Business Intelligence tools help the organizations to answer questions such as where the organization stands in terms of profitability, growth status, brand & market position and market segment. Business intelligence tools focuses mainly on the past or current data and try to explore the hidden insight from the data. Business intelligence tools include querying, reporting, online analytics and data visualization tools which help the business decision makers to arrive at informed decision about the impact and status of their strategies. This book starts with the introduction of business intelligence concepts, components of business intelligence system, business intelligence tools used for querying, reporting and visualization of data. It provides an overview of the data visualization and data mining methods like classification, clustering and regression methods using R open source software. Book also covers some of the basic descriptive and inferential statistical tools. It focuses on both managerial side and technological side of BI. Vinaitheerthan Renganathan www.vinatheerthan.com/book.php