Modern Management Based on Big Data IV
Modern Management Based on Big Data IV

Author: A.J. Tallón-Ballesteros

Publisher: IOS Press

Published: 2023-08-23

Total Pages: 484

ISBN-13: 1643684116

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The concept of Big Data has become increasingly familiar in recent years, and it is already an indispensible tool in the management of everything from supply chains and transport to health and education. This book presents the proceedings of MMBD 2023, the 4th International Conference on Modern Management based on Big Data, held in Seoul, South Korea, from 1-4 August 2023. The 50 papers included here were selected from total of around 160 submissions after a rigorous review process. Papers delivered at the conference were divided into 3 main categories: Big Data, Modern Management, and a special session devoted to Big Data-driven manufacturing and service-industry supply-chain (SC) management, but in addition to these general topics, there were also a number of papers related to lifelong education. Topics covered in the book include innovation in online education management with big data; digital transformation in lifelong education; big data analysis in lifelong education management; green supply chain management; big data analytics in supply chains; policy and strategy for new energy and the environment; smart grid load and energy management; decision-making on sustainable transport policies; modern healthcare management; and social strategy to manage human relationships. Of particular interest are papers concerning big-data analysis and emerging applications. Presenting innovative original ideas and methods, together with significant results, and supported by clear and rigorous reasoning and compelling new evidence, the book will be of interest to all those who use Big Data to support their management strategies.

Information Management and Big Data
Information Management and Big Data

Author: Juan Antonio Lossio-Ventura

Publisher: Springer Nature

Published: 2021-05-11

Total Pages: 563

ISBN-13: 3030762289

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This book constitutes the refereed proceedings of the 7th International Conference on Information Management and Big Data, SIMBig 2020, held in Lima, Peru, in October 2020.* The 32 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 122 submissions. The papers address topics such as natural language processing and text mining; machine learning; image processing; social networks; data-driven software engineering; graph mining; and Semantic Web, repositories, and visualization. *The conference was held virtually.

Fraud Prevention in Online Digital Advertising
Fraud Prevention in Online Digital Advertising

Author: Xingquan Zhu

Publisher: Springer

Published: 2017-06-08

Total Pages: 61

ISBN-13: 3319567934

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The authors systematically review methods of online digital advertising (ad) fraud and the techniques to prevent and defeat such fraud in this brief. The authors categorize ad fraud into three major categories, including (1) placement fraud, (2) traffic fraud, and (3) action fraud. It summarizes major features of each type of fraud, and also outlines measures and resources to detect each type of fraud. This brief provides a comprehensive guideline to help researchers understand the state-of-the-art in ad fraud detection. It also serves as a technical reference for industry to design new techniques and solutions to win the battle against fraud.

Intelligent Systems Modeling and Simulation II
Intelligent Systems Modeling and Simulation II

Author: Samsul Ariffin Abdul Karim

Publisher: Springer Nature

Published: 2022-10-12

Total Pages: 688

ISBN-13: 3031040287

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This book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations.

Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting
Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

Author: Jun Wang

Publisher:

Published: 2017-07-13

Total Pages: 158

ISBN-13: 9781680833102

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This monograph offers insightful knowledge of real-world RTB systems, to bridge the gaps between industry and academia, and to provide an overview of the fundamental infrastructure, algorithms, and technical and research challenges of the new frontier of computational advertising.

Programmatic Advertising
Programmatic Advertising

Author: Oliver Busch

Publisher: Springer

Published: 2015-11-26

Total Pages: 280

ISBN-13: 331925023X

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This fundamental guide on programmatic advertising explains in detail how automated, data-driven advertising really works in practice and how the right adoption leads to a competitive advantage for advertisers, agencies and media. The new way of planning, steering and measuring marketing may still appear complex and threatening but promising at once to most decision makers. This collaborative compendium combines proven experience and best practice in 22 articles written by 45 renowned experts from all around the globe. Among them Dr. Florian Heinemann/Project-A, Peter Würtenberger/Axel-Springer, Deirdre McGlashan/MediaCom, Dr. Marc Grether/Xaxis, Michael Lamb/MediaMath, Carolin Owen/IPG, Stefan Bardega/Zenith, Arun Kumar/Cadreon, Dr. Ralf Strauss/Marketingverband, Jonathan Becher/SAP and many more great minds.

Python Data Science Handbook
Python Data Science Handbook

Author: Jake VanderPlas

Publisher: "O'Reilly Media, Inc."

Published: 2016-11-21

Total Pages: 609

ISBN-13: 1491912138

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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Handbook of Marketing Decision Models
Handbook of Marketing Decision Models

Author: Berend Wierenga

Publisher: Springer Science & Business Media

Published: 2008-09-05

Total Pages: 621

ISBN-13: 0387782133

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Marketing models is a core component of the marketing discipline. The recent developments in marketing models have been incredibly fast with information technology (e.g., the Internet), online marketing (e-commerce) and customer relationship management (CRM) creating radical changes in the way companies interact with their customers. This has created completely new breeds of marketing models, but major progress has also taken place in existing types of marketing models. Handbook of Marketing Decision Models presents the state of the art in marketing decision models. The book deals with new modeling areas, such as customer relationship management, customer value and online marketing, as well as recent developments in other advertising, sales promotions, sales management, and competition are dealt with. New developments are in consumer decision models, models for return on marketing, marketing management support systems, and in special techniques such as time series and neural nets.

Click Models for Web Search
Click Models for Web Search

Author: Aleksandr Chuklin

Publisher: Morgan & Claypool Publishers

Published: 2015-07-01

Total Pages: 117

ISBN-13: 1627056483

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With the rapid growth of web search in recent years the problem of modeling its users has started to attract more and more attention of the information retrieval community. This has several motivations. By building a model of user behavior we are essentially developing a better understanding of a user, which ultimately helps us to deliver a better search experience. A model of user behavior can also be used as a predictive device for non-observed items such as document relevance, which makes it useful for improving search result ranking. Finally, in many situations experimenting with real users is just infeasible and hence user simulations based on accurate models play an essential role in understanding the implications of algorithmic changes to search engine results or presentation changes to the search engine result page. In this survey we summarize advances in modeling user click behavior on a web search engine result page. We present simple click models as well as more complex models aimed at capturing non-trivial user behavior patterns on modern search engine result pages. We discuss how these models compare to each other, what challenges they have, and what ways there are to address these challenges. We also study the problem of evaluating click models and discuss the main applications of click models.