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Business Intelligence
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and ...
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tübingen, Germany, in April 2009 colocated with the Evo* 2009 events. The 17 revised full papers were carefully reviewed and selected from 44 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain, April 2007. Coverage brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.
Pattern Recognition in Bioinformatics
This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition in Bioinformatics, PRIB 2010, held in Nijmegen, The Netherlands, in September 2010. The 38 revised full papers presented were carefully reviewed and selected from 46 submissions. The field of bioinformatics has two main objectives: the creation and maintenance of biological databases and the analysis of life sciences data in order to unravel the mysteries of biological function. Computer science methods such as pattern recognition, machine learning, and data mining have a great deal to offer the field of bioinformatics.
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
The ?eld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences datainordertounravelthemysteriesofbiologicalfunction,leadingtonewdrugs andtherapiesforhumandisease. Life sciencesdatacomeinthe formofbiological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model speci'c information in a given dataset in order to generate new interesting knowledge. Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to o'er the ?eld of bioinformatics. The goal of the 8th - ropean ...
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learning; ensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques
This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.
AI-Based Data Analytics
This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based bu...
Advances in Data Mining - Theoretical Aspects and Applications
The papers in this volume represent the proceedings of the 7th Industrial Conference on Data Mining. They are organized into topical sections on aspects of classification and prediction, clustering, web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Readers gain new insights into theories underlying data mining and discover state-of-the-technology applications.
