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Author: Madhura Janardan Maideo
Publisher:
ISBN:
Category :
Languages : en
Pages : 222
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Book Description
Emerging data mining techniques need to identify and react to changes in surrounding environments and cater to the dynamic and evolving nature of datasets. This is referred to as context aware data mining. Some of the major challenges are 1) lack of established models to recognize context, 2) difficulty in converting context into machine processable representation and 3) lack of methodologies to represent such context within data mining process. To address these challenges, we built a semantic framework that creates ontological context model to categorize context parameters into context groups and attributes. Individual attributes are mapped onto underlying databases to first create and then mine the context aware datasets. As a proof of concept, we have developed a prototype based on the case studies from cardiac domain. We conclude that when context aware datasets are mined, new interesting patterns are revealed that were not present in traditional data mining approaches.
Author: Madhura Janardan Maideo
Publisher:
ISBN:
Category :
Languages : en
Pages : 222
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Book Description
Emerging data mining techniques need to identify and react to changes in surrounding environments and cater to the dynamic and evolving nature of datasets. This is referred to as context aware data mining. Some of the major challenges are 1) lack of established models to recognize context, 2) difficulty in converting context into machine processable representation and 3) lack of methodologies to represent such context within data mining process. To address these challenges, we built a semantic framework that creates ontological context model to categorize context parameters into context groups and attributes. Individual attributes are mapped onto underlying databases to first create and then mine the context aware datasets. As a proof of concept, we have developed a prototype based on the case studies from cardiac domain. We conclude that when context aware datasets are mined, new interesting patterns are revealed that were not present in traditional data mining approaches.
Author: Yanan Yin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Leslie F. Sikos
Publisher: Springer Nature
ISBN: 3030676811
Category : Computers
Languages : en
Pages : 110
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Book Description
RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Author: Faisal Lugman
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Panayiotis Vlamos
Publisher: Springer
ISBN: 3319573489
Category : Medical
Languages : en
Pages : 294
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Book Description
The 2nd World Congress on Genetics, Geriatrics and Neurodegenerative Disease Research (GeNeDis 2016), will focus on recent advances in geriatrics and neurodegeneration, ranging from basic science to clinical and pharmaceutical developments and will provide an international focum for the latest scientific discoveries, medical practices, and care initiatives. Advances information technologies will be discussed along with their implications for various research, implementation, and policy concerns. In addition, the conference will address European and global issues in the funding of long-term care and medico-social policies regarding elderly people. GeNeDis 2016 takes place in Sparta, Greece, 20-23 October, 2016. This volume focuses on the sessions that address geriatrics.
Author: Phan Cong Vinh
Publisher: Springer Nature
ISBN: 303093179X
Category : Computers
Languages : en
Pages : 347
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Book Description
This book constitutes the refereed post-conference proceedings of the International Conference on Context-Aware Systems and Applications, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 25 revised full papers presented were carefully selected from 52 submissions. The papers cover a wide spectrum of modern approaches and techniques for smart computing systems and their applications.
Author: Grzegorz J. Nalepa
Publisher: Springer
ISBN: 331966655X
Category : Technology & Engineering
Languages : en
Pages : 453
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Book Description
This book proposes a consistent methodology for building intelligent systems. It puts forward several formal models for designing and implementing rules-based systems, and presents illustrative case studies of their applications. These include software engineering, business process systems, Semantic Web, and context-aware systems on mobile devices. Rules offer an intuitive yet powerful method for representing human knowledge, and intelligent systems based on rules have many important applications. However, their practical development requires proper techniques and models - a gap that this book effectively addresses.
Author: Longbing Cao
Publisher: Springer Science & Business Media
ISBN: 0387794204
Category : Computers
Languages : en
Pages : 310
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Book Description
Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
Author: Emmanouel Garoufallou
Publisher: Springer
ISBN: 3319491571
Category : Computers
Languages : en
Pages : 387
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Book Description
This book constitutes the refereed proceedings of the 10th Metadata and Semantics Research Conference, MTSR 2016, held in Göttingen, Germany, in November 2016. The 26 full papers and 6 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in several sessions and tracks: Digital Libraries, Information Retrieval, Linked and Social Data, Metadata and Semantics for Open Repositories, Research Information Systems and Data Infrastructures, Metadata and Semantics for Agriculture, Food and Environment, Metadata and Semantics for Cultural Collections and Applications, European and National Projects.
Author: Huan Liu
Publisher: Springer Science & Business Media
ISBN: 1461556899
Category : Computers
Languages : en
Pages : 225
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Book Description
As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.
