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Heuristics In Analytics

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Heuristics In Analytics

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Author : Carlos Andre Reis Pinheiro
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-03

Heuristics In Analytics written by Carlos Andre Reis Pinheiro and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-03 with Business & Economics categories.

Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more. Robust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. Heuristics in Analytics describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to: Realize just how random the world is, and how unplanned events can affect analysis Integrate heuristic and analytical approaches to modeling and problem solving Discover how graph analysis is applied in real-world scenarios around the globe Apply analytical knowledge to customer behavior, insolvency prevention, fraud detection, and more Understand how text analytics can be applied to increase the business knowledge Every single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, Heuristics in Analytics contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.

Heuristics In Analytics

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Author : Carlos Andre Reis Pinheiro
language : en
Publisher: John Wiley & Sons
Release Date : 2014-01-31

Metaheuristics For Business Analytics

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Author : Abraham Duarte
language : en
Publisher: Springer
Release Date : 2017-11-24

Metaheuristics For Business Analytics written by Abraham Duarte and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-24 with Business & Economics categories.

This essential metaheuristics tutorial provides descriptions and practical applications in the area of business analytics. It addresses key problems in predictive and prescriptive analysis, while also illustrating how problems that arise in business analytics can be modelled and how metaheuristics can be used to find high-quality solutions. Readers will be introduced to decision-making problems for which metaheuristics offer the most effective solution technique. The book not only shows business problem modelling on a spreadsheet but also how to design and create a Visual Basic for Applications code. Extra Material can be downloaded at http://extras.springer.com/978-3-319-68117-7.

Theory Of Randomized Search Heuristics

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Author : Anne Auger
language : en
Publisher: World Scientific
Release Date : 2011

Theory Of Randomized Search Heuristics written by Anne Auger and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.

This volume covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence.

Judgment Under Uncertainty

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Author : Daniel Kahneman
language : en
Publisher: Cambridge University Press
Release Date : 1982-04-30

Judgment Under Uncertainty written by Daniel Kahneman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-04-30 with Psychology categories.

Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.

Business And Consumer Analytics New Ideas

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Author : Pablo Moscato
language : en
Publisher: Springer
Release Date : 2019-05-13

Business And Consumer Analytics New Ideas written by Pablo Moscato and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-13 with Computers categories.

This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.

Analytics And Intuition In The Process Of Selecting Talent

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Author : Jürgen Deters
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-11-07

Analytics And Intuition In The Process Of Selecting Talent written by Jürgen Deters and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-07 with Business & Economics categories.

Human decisions, especially in management and personnel selection, are based on making judgments about people analytically and intuitively. Yet in business and scientific contexts, judgments are expected to be based on a rational analysis rather than intuitions or emotions. Intuition is often seen as something mystical that should not be trusted and thus eliminated from human decision-making. Our empirical and theoretical research shows that this is impossible when people are dealing with people. Instead, intuitions and emotions have significant power in the decision-making process. Neuroscience even shows that humans are incapable of switching off their emotions or intuitions when making decisions. Therefore, intuition and emotions as evolutionary achievements of human beings should be looked at more closely to use the wisdom they offer. This book provides an insight into the current state of research on rational-analytical procedures in personnel selection and complements this with research on intuitions and emotions in personnel diagnostics. By integrating scientifically verifiable rational-analytical decision-making procedures with the inner experiential knowledge of people, this book bridges two complementary ways of recognizing and making good decisions. It demonstrates how intuitions are developed and used in different fields of practice and cultures and how scientific research results from rational-analytical and intuitive-emotional selection procedures are successfully integrated by practitioners.

Massive Graph Analytics

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Author : David A. Bader
language : en
Publisher: CRC Press
Release Date : 2022-07-20

Massive Graph Analytics written by David A. Bader and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Business & Economics categories.

"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.

Big Data Analytics And Knowledge Discovery

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Author : Carlos Ordonez
language : en
Publisher: Springer
Release Date : 2018-08-20

Big Data Analytics And Knowledge Discovery written by Carlos Ordonez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-20 with Computers categories.

This book constitutes the refereed proceedings of the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2018, held in Regensburg, Germany, in September 2018. The 13 revised full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers are organized in the following topical sections: Graph analytics; case studies; classification and clustering; pre-processing; sequences; cloud and database systems; and data mining.

Business Analytics For Decision Making

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Author : Steven Orla Kimbrough
language : en
Publisher: CRC Press
Release Date : 2018-09-03

Business Analytics For Decision Making written by Steven Orla Kimbrough and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Business & Economics categories.

Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.

Heuristics In Analytics

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