12,851 Hits in 12.1 sec

Supporting an Expert-centric Process of New Product Introduction With Statistical Machine Learning

Shima Zahmatkesh, Alessio Bernardo, Emanuele Falzone, Edgardo Di Nicola Carena, Emanuele Della Valle
2021 Business Information Systems  
Traditionally, NPI is an expertcentric process. This paper presents a study on automating the forecast of NPI demands using statistical Machine Learning (namely, Gradient Boosting and XGBoost).  ...  Finally, we provide empirical evidence that statistical Machine Learning can forecast NPI demand better than experts.  ...  Utilizing the statistical Machine Learning, is it possible to improve the demand forecast for New Product Introduction done by the experts?  ... 
doi:10.52825/bis.v1i.57 fatcat:2sp6iflzkjf3hm7ek3kksreom4

Desiderata for Explainable AI in statistical production systems of the European Central Bank [article]

Carlos Mougan, Georgios Kanellos, Thomas Gottron
2022 arXiv   pre-print
In this work, we aim to state clear user-centric desiderata for explainable AI reflecting common explainability needs experienced in statistical production systems of the European Central Bank.  ...  To this end, we provide two concrete use cases from the domain of statistical data production in central banks: the detection of outliers in the Centralised Securities Database and the data-driven identification  ...  Statistical production systems rely on domain experts with an outstanding understanding of the data.  ... 
arXiv:2107.08045v2 fatcat:kz5ux27ngbfwrhx7bblblrul44

Data-driven Design and Curation for Consumer-centric Fast Fashion

Fredrick Shaap
2020 Current Trends in Fashion Technology & Textile Engineering  
The data-driven, consumer-centric characteristics of these concepts are emphasized and the design process flowcharts for some key examples of related current and popular methodologies are presented and  ...  The principles and concepts concerning creation and curation of optimal design for the fast fashion business model are reviewed and discussed briefly.  ...  In some cases [2] , a framework consisting of artificial intelligence, machine-learning and data analytics combined with expert curation creates the most optimal design for its intended purpose.  ... 
doi:10.19080/ctftte.2019.05.555706 fatcat:6wb5m2rzgbhxzbnn6yjfp7iqsi

Spreadsheet interfaces for usable machine learning

Advait Sarkar
2015 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)  
However, they are often unable to do so due to the lack of usable tools for statistical non-experts.  ...  In the 21st century, it is common for people of many professions to have interesting datasets to which machine learning models may be usefully applied.  ...  as well as statistics and machine learning.  ... 
doi:10.1109/vlhcc.2015.7357228 dblp:conf/vl/Sarkar15 fatcat:6rngju7plvah7ol5urydjttbre

Developing Talents vis-à-vis Fourth Industrial Revolution

Muhammad Anshari, Mohammad Nabil Almunawar, Abdur Razzaq
2021 International Journal of Asian Business and Information Management  
The proposed model defined that clusters of machine-centric are jobs performed routinely on an application basis and usually structured and do not require any compassion or emotions.  ...  With the arrival of the Fourth Industrial Revolution (4IR) many believed that 4IR might increase the unemployment rate by replacing the current jobs with automated machines such as robots whereas some  ...  While, the data and machine learning fueled and supported it.  ... 
doi:10.4018/ijabim.20211001.oa2 fatcat:z65go2qd75eo3hswe6j5huaweu

Data-Centric Explanations: Explaining Training Data of Machine Learning Systems to Promote Transparency

Ariful Islam Anik, Andrea Bunt
2021 Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems  
Training datasets fundamentally impact the performance of machine learning systems.  ...  In this thesis, I explore the concept of data-centric explanations for machine learning systems that describe the training data to end-users.  ...  Productivity and selection of human capital with machine learning. American Economic Review 106, 5: 124-127. 18.  ... 
doi:10.1145/3411764.3445736 fatcat:kkhfs4es55ht3ibljq7wzpttgy

Data-centric decision support

R. Kulhavy
2002 Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301)  
The paper deals with both methodological and practical aspects of design, implementation and application of datacentric decision support systems powered by the historical process and business data.  ...  The paper is written from the product development and corporate R&D perspective and discusses major decisions and traps on the developers' way from the original idea to its commercial use.  ...  Think of a complex production schema composed of multiple processes with different dynamics.  ... 
doi:10.1109/acc.2002.1025318 fatcat:6odf3hdayzfktplxpg4u6jyxte

Industrial Challenges In Human-Centred Production

Wolfgang Unzeitig, Martin Wifling, Alexander Stocker, Manfred Rosenberger
2015 Zenodo  
Supporting production workers through providing them with action relevant data, information and knowledge via modern information technology has become a central topic of research.  ...  mobile learning in the production.  ...  These solution will then be rolled out as pilot in the different production sites of the industrial project partners.  ... 
doi:10.5281/zenodo.820998 fatcat:7yqt774o4fdntpwggwmnnsisma

Human-Centric Artificial Intelligence Architecture for Industry 5.0 Applications [article]

Jože M. Rožanec, Inna Novalija, Patrik Zajec, Klemen Kenda, Hooman Tavakoli, Sungho Suh, Entso Veliou, Dimitrios Papamartzivanos, Thanassis Giannetsos, Sofia Anna Menesidou, Ruben Alonso, Nino Cauli (+8 others)
2022 arXiv   pre-print
Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0.  ...  Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and human-centricity at its core.  ...  To enable demand forecasts, we developed multiple statistical and machine learning models for products with smooth and erratic demands (Rožanec et al. (2021a) ).  ... 
arXiv:2203.10794v1 fatcat:xt2gbrdi5vekbchzisrhq5yx2q

Introducing Data-Centric Engineering: An open access journal dedicated to the transformation of engineering design and practice

Mark Girolami
2020 Data-Centric Engineering  
Impact Statement Data-Centric Engineering is a peer-reviewed, open access journal for work that promotes the use of experimental and observational data-and new methods of sensing, measurement, and data  ...  capture-in all areas of engineering in order to design systems and products that are more reliable, resilient, efficient and safe.  ...  Data availability is not applicable to this article as no new data were created or analyzed in this study.  ... 
doi:10.1017/dce.2020.5 fatcat:fwkkdv46ovbvngippofz3jvuzm

A Perspective on Cyberinfrastructure for Water Research Driven by Informatics Methodologies

Peter Bajcsy
2008 Geography Compass  
In the digital era and within the context of CI, the scientific productivity is often determined by the efficiency of data-centric and collaborationcentric activities.  ...  We present the concepts of data-centric and collaboration-centric activities supported by concrete examples, and outline the challenges and requirements on CI driven by these informatics activities.  ...  Fig. 1 . 1 Typical flow of a learning process in earth sciences. Fig. 2 . 2 An example of top-level data-centric and collaboration-centric activities.  ... 
doi:10.1111/j.1749-8198.2008.00160.x fatcat:cvqt7yhvgvfi3glceyc3huhlxy

Artificial Intelligence in Business: A Literature Review and Research Agenda

Quynh N. Nguyen, School of Business, Stockton University, Anna Sidorova, Russell Torres, G. Brint Ryan College of Business University of North Texas, G. Brint Ryan College of Business University of North Texas
2022 Communications of the Association for Information Systems  
The rise of artificial intelligence (AI) technologies has created promising research opportunities for the information systems (IS) discipline.  ...  learning and data classification learning,+classification,+machine,data,+text A05 Decision support systems and knowledge management +system,+decision,knowledge,+support,+process Table 2 .  ...  The product-centric view focuses on the social actors, processes, and interactions that surround AI but do not assign AI an active role.  ... 
doi:10.17705/1cais.05007 fatcat:ws737ndiffezzjtvsgieth35ou

InfoXtract: A customizable intermediate level information extraction engine

2006 Natural Language Engineering  
These new tasks also facilitate the correlation of output from an IE engine with existing structured data. Benchmarking results for the core engine and applications utilizing the engine are presented.  ...  This paper focuses on IE tasks designed to support information discovery applications.  ...  Acknowledgments The authors wish to thank Carrie Pine of AFRL for reviewing and supporting this work.  ... 
doi:10.1017/s1351324906004116 fatcat:f7xidowuffc2bfalikhzdxhw3y

Towards a Human-Centric Design Framework for AI Assisted Music Production

Augoustinos Tsiros, Alessandro Palladini
2020 Proceedings of the International Conference on New Interfaces for Musical Expression  
and the design of tools that support creativity in music production.  ...  We demonstrate how these principles have been applied to inform the design of the interaction between expert live audio mixing engineers with the Channel-AI (i.e. a corpus of AI features embedded in the  ...  CONCLUSSIONS The best approach to the design and evaluation of human-centric AI for expert users is an open question for debate.  ... 
doi:10.5281/zenodo.4813435 fatcat:7ggdbogjdbcanjysrounpmyh7m

Instructional Model for Building Effective Big Data Curricula for Online and Campus Education

Yuri Demchenko, Emanuel Gruengard, Sander Klous
2014 2014 IEEE 6th International Conference on Cloud Computing Technology and Science  
in cooperation with KPMG and by the Laureate Online Education (online partner of the University of Liverpool).  ...  This paper presents current results and ongoing work to develop effective educational courses on the Big Data (BD) and Data Intensive Technologies (DIT) that is been done at the University of Amsterdam  ...  statistical methods, machine learning and predictions.  ... 
doi:10.1109/cloudcom.2014.162 dblp:conf/cloudcom/DemchenkoGK14 fatcat:lfrm2c2tkjfs5o3qrzb455sszu
« Previous Showing results 1 — 15 out of 12,851 results