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Uncertainty and Graphing in Discovery Work

Uncertainty and Graphing in Discovery Work
Author: Wolff-Michael Roth
Publisher: Springer
Total Pages: 462
Release: 2014-08-08
Genre: Science
ISBN: 940077009X

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This book deals with uncertainty and graphing in scientific discovery work from a social practice perspective. It is based on a 5-year ethnographic study in an advanced experimental biology laboratory. The book shows how, in discovery work where scientists do not initially know what to make of graphs, there is a great deal of uncertainty and scientists struggle in trying to make sense of what to make of graphs. Contrary to the belief that scientists have no problem “interpreting” graphs, the chapters in this book make clear that uncertainty about their research object is tied to uncertainty of the graphs. It may take scientists several years of struggle in their workplace before they find out just what their graphs are evidence of. Graphs turn out to stand to the entire research in a part/whole relation, where scientists not only need to be highly familiar with the context from which their data are extracted but also with the entire process by means of which the natural world comes to be transformed and represented in the graph. This has considerable implications for science, technology, engineering, and mathematics education at the secondary and tertiary level, as well as in vocational training. This book discusses and elaborates these implications.


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Hisashi Kashima
Publisher: Springer Nature
Total Pages: 563
Release: 2023-05-27
Genre: Computers
ISBN: 3031333772

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The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023. The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Hady W. Lauw
Publisher: Springer Nature
Total Pages: 936
Release: 2020-05-08
Genre: Computers
ISBN: 3030474364

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The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.


Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases
Author: Michele Berlingerio
Publisher: Springer
Total Pages: 866
Release: 2019-01-22
Genre: Computers
ISBN: 3030109283

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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.


Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery
Author: Yong Liu
Publisher: Springer Nature
Total Pages: 1004
Release: 2019-11-06
Genre: Technology & Engineering
ISBN: 3030324567

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This book discusses the recent advances in natural computation, fuzzy systems and knowledge discovery. Presenting selected, peer-reviewed papers from the 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019), held in Kunming, China, from 20 to 22 July 2019, it is a useful resource for researchers, including professors and graduate students, as well as R&D staff in industry.


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Qiang Yang
Publisher: Springer
Total Pages: 648
Release: 2019-04-03
Genre: Computers
ISBN: 3030161455

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The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.


Machine Learning and Knowledge Discovery in Databases: Research Track

Machine Learning and Knowledge Discovery in Databases: Research Track
Author: Danai Koutra
Publisher: Springer Nature
Total Pages: 754
Release: 2023-09-16
Genre: Computers
ISBN: 3031434188

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The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: ​Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: ​Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: ​Robustness; Time Series; Transfer and Multitask Learning. Part VI: ​Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. ​Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.


Picturing the Uncertain World

Picturing the Uncertain World
Author: Howard Wainer
Publisher: Princeton University Press
Total Pages: 264
Release: 2011-10-30
Genre: Mathematics
ISBN: 0691152675

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From the publisher. This book explores how graphs can serve as maps to guide us when the information we have is ambiguous or incomplete. Using a visually diverse sampling of graphical display, from heartrending autobiographical displays of genocide in the Kovno ghetto to the "Pie Chart of Mystery" in a New Yorker cartoon, Wainer illustrates the many ways graphs can be used--and misused--as we try to make sense of an uncertain world. Picturing the Uncertain World takes readers on an extraordinary graphical adventure, revealing how the visual communication of data offers answers to vexing questions yet also highlights the measure of uncertainty in almost everything we do. Are cancer rates higher or lower in rural communities? How can you know how much money to sock away for retirement when you don't know when you'll die? And where exactly did nineteenth-century novelists get their ideas? These are some of the fascinating questions Wainer invites readers to consider. Along the way he traces the origins and development of graphical display, from William Playfair, who pioneered the use of graphs in the eighteenth century, to instances today where the public has been misled through poorly designed graphs.


Cognition, Assessment and Debriefing in Aviation

Cognition, Assessment and Debriefing in Aviation
Author: Wolff-Michael Roth
Publisher: CRC Press
Total Pages: 474
Release: 2017-07-20
Genre: Technology & Engineering
ISBN: 1351807021

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Debriefing is a major component of the job in many high-risk industries where errors can have considerable, often deadly consequences, including combat, surgery, and aviation. Although there exists considerable literature on debriefing, recent reviews of the literature suggest (a) shortcomings in the topics researched, (b) paucity of related theory, (c) limitations in the number of empirical studies, and (d) problems in research design. There are also recent suggestions that "there are surprisingly studies in the scholarly literature that show how to debrief, how to teach or learn to debrief, what methods of debriefing exists and how effective they are at achieving learning objectives and goals" Meta-analyses reveal substantial variations in research findings—e.g., on the use of video as a means of debriefing—that can be traced to the problems. This book redresses these problems in that it provides a detailed look at debriefing and assessment, the functions of different cognitive artifacts used, and a theoretical framework that accounts for the complexity of flying an aircraft and for the debriefing of the pilots’ experiences, especially under the high-stakes condition of their bi-annual evaluation for licensing purposes. The book provides detailed investigation of flight examiners’ methods to arrive at assessments of aviation pilot performance. It shows and theoretically models why there are good reasons for lower than desired inter-rater agreements. It offers detailed scenarios of how debriefing can be made to draw maximum benefit for pilot learning, that is, for the take-home messages that will make them better pilots. The theoretical framework includes objective factors that determine performance and the subjective experience pilots have while undergoing training and testing in flight simulators


Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases
Author: Wray Buntine
Publisher: Springer
Total Pages: 787
Release: 2009-08-27
Genre: Computers
ISBN: 3642041744

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This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.