New Trends in Computational Collective Intelligence PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download New Trends in Computational Collective Intelligence PDF full book. Access full book title New Trends in Computational Collective Intelligence by David Camacho. Download full books in PDF and EPUB format.
Author: David Camacho
Publisher: Springer
ISBN: 3319107747
Category : Technology & Engineering
Languages : en
Pages : 210
Get Book Here
Book Description
This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods and Applications, Computer Vision, and Intelligent Computational Methods. This book will be useful for graduate and PhD students in computer science as well as for mature academics, researchers and practitioners interested in the methods and applications of collective computational intelligence in order to create new intelligent systems.
Author: David Camacho
Publisher: Springer
ISBN: 3319107747
Category : Technology & Engineering
Languages : en
Pages : 210
Get Book Here
Book Description
This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods and Applications, Computer Vision, and Intelligent Computational Methods. This book will be useful for graduate and PhD students in computer science as well as for mature academics, researchers and practitioners interested in the methods and applications of collective computational intelligence in order to create new intelligent systems.
Author: Anne-Sophie Hadaschik
Publisher:
ISBN:
Category :
Languages : en
Pages : 55
Get Book Here
Book Description
The increasing occurrence of customer churn that implies customers' discontinuation of their current relationship with a service provider, has forced many companies in competitive markets to redirect their strategic focus to consider customer acquisition and customer retention equally. In particular, in the telecommunication industry a high degree of saturation and competition contributed to ever increasing churn rates. However, resources of marketing managers to develop valid churn prediction and retention techniques are finite. The aim of this study is to identify customers which are likely to churn with a constrained and thus limited set of characteristics. Therefore, this study investigates the churn behavior of customers of a German telecommunication company. The study's finding underline the usefulness of logistic regression when building a churn prediction model. Furthermore, the research shows that a limited number of explanatory variables are sufficient to predict churn with proficient accuracy so that companies may carry out suitable actions to prevent customer churn. In detail, the study identifies a distinct correlation between customer churn behavior and attributes of customer contract history, as well as certain demographic variables. In order to focus on profitable customers when managing churn, a classification approach is computed to improve marketing spending. This thesis encourages companies to justify or expand measurements against churn by proposing an easier and more cost-effective means for customer churn prediction.
Author: Mukesh K. Mohania
Publisher: Springer
ISBN: 3642037305
Category : Computers
Languages : en
Pages : 493
Get Book Here
Book Description
Data warehousing and knowledge discovery are increasingly becoming mission-critical technologies for most organizations, both commercial and public, as it becomes incre- ingly important to derive important knowledge from both internal and external data sources. With the ever growing amount and complexity of the data and information available for decision making, the process of data integration, analysis, and knowledge discovery continues to meet new challenges, leading to a wealth of new and exciting research challenges within the area. Over the last decade, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has established itself as one of the most important international scientific events within data warehousing and knowledge discovery. DaWaK brings together a wide range of researchers and practitioners working on these topics. The DaWaK conference series thus serves as a leading forum for discu- ing novel research results and experiences within data warehousing and knowledge th discovery. This year’s conference, the 11 International Conference on Data Wa- housing and Knowledge Discovery (DaWaK 2009), continued the tradition by d- seminating and discussing innovative models, methods, algorithms, and solutions to the challenges faced by data warehousing and knowledge discovery technologies.
Author: Tai-hoon Kim
Publisher: Springer
ISBN: 3642356036
Category : Computers
Languages : en
Pages : 371
Get Book Here
Book Description
This volume constitutes the refereed proceedings of the International Conferences, EL, DTA and UNESST 2012, held as part of the Future Generation Information Technology Conference, FGIT 2012, Kangwondo, Korea, in December 2012. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of education and learning, database theory and application and u- and e-service, science and technology.
Author: Ashish Khanna
Publisher: Springer Nature
ISBN: 9811503249
Category : Technology & Engineering
Languages : en
Pages : 599
Get Book Here
Book Description
This book gathers high-quality research papers presented at the Second International Conference on Innovative Computing and Communication (ICICC 2019), which was held at the VSB - Technical University of Ostrava, Czech Republic, on 21–22 March 2019. Highlighting innovative papers by scientists, scholars, students, and industry experts in the fields of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research, and the translation of applied research into real-world applications.
Author: Longbing Cao
Publisher: Springer
ISBN: 3642173136
Category : Computers
Languages : en
Pages : 589
Get Book Here
Book Description
With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
Author: Xin-She Yang
Publisher: Springer Nature
ISBN: 9811621020
Category : Technology & Engineering
Languages : en
Pages : 883
Get Book Here
Book Description
This book gathers selected high-quality research papers presented at the Sixth International Congress on Information and Communication Technology, held at Brunel University, London, on February 25–26, 2021. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The book is presented in four volumes.
Author: Rajesh Kumar Shukla
Publisher: Springer Nature
ISBN: 9811520712
Category : Technology & Engineering
Languages : en
Pages : 789
Get Book Here
Book Description
This book presents a selection of revised and extended versions of the best papers from the First International Conference on Social Networking and Computational Intelligence (SCI-2018), held in Bhopal, India, from October 5 to 6, 2018. It discusses recent advances in scientific developments and applications in these areas.
Author: Shuigeng Zhou
Publisher: Springer Science & Business Media
ISBN: 3642355277
Category : Computers
Languages : en
Pages : 812
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.
Author: David D. Denison
Publisher: Springer Science & Business Media
ISBN: 0387215794
Category : Mathematics
Languages : en
Pages : 465
Get Book Here
Book Description
Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future.
