On Uncertain Graphs, Arijit Khan, Yuan Ye, Lei Chen
Автор: Arijit Khan, Yuan Ye, Lei Chen Название: On Uncertain Graphs ISBN: 1681730375 ISBN-13(EAN): 9781681730370 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 46200.00 T Наличие на складе: Невозможна поставка. Описание: Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
Автор: Yue, Kun (yunnan Univ, China) Liu, Weiyi (yunnan Univ, China) Wu, Hao (yunnan Univ, China) Название: Discovery and fusion of uncertain knowledge in data ISBN: 9813227125 ISBN-13(EAN): 9789813227125 Издательство: World Scientific Publishing Рейтинг: Цена: 81310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data analysis is of upmost importance in the mining of big data, where knowledge discovery and inference are the basis for intelligent systems to support the real world applications. However, the process involves knowledge acquisition, representation, inference and data, Bayesian network (BN) is the key technology plays a key role in knowledge representation, in order to pave way to cope with incomplete, fuzzy data to solve the real-life problems.
This book presents Bayesian network as a technology to support data-intensive and incremental learning in knowledge discovery, inference and data fusion in uncertain environment.
Автор: Jeff Z. Pan; Guido Vetere; Jose Manuel Gomez-Perez Название: Exploiting Linked Data and Knowledge Graphs for Large Organisations ISBN: 3319456520 ISBN-13(EAN): 9783319456522 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and "standard" data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.
Автор: Chen Название: Group Decision and Negotiation in an Uncertain World ISBN: 3319928732 ISBN-13(EAN): 9783319928739 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Theoretical Concepts of Group Decision and Negotiation.- Hesitant Fuzzy Linguistic Group Decision Making with Borda Rule.- A Multistage Risk Decision Making Method for Normal Cloud Model with Three Reference Points.- System Portfolio Selection under Hesitant Fuzzy Information.- Decision Support and Behavior in Group Decision and Negotiation Representative Decision-making and the Propensity to Use Round and Sharp Numbers in Preference Specification. -Neuroscience Experiment for Graphical Visualization in the FITradeoff Decision Support System.- Impact of Negotiators' Predispositions on Their Efforts and Outcomes in Bilateral Online Negotiations.- Some Methodological Considerations for the Organization and Analysis of Inter- and Intra-cultural Negotiation Experiments.- FITradeoff Method for the Location of Healthcare Facilities based on Multiple Stakeholders' Preferences.- Capturing the Participants' Voice: Using Causal Mapping supported by Group Decision Software to enhance Procedural Justice.- The Effects of Photographic Images on Agent to Human Negotiations: The Case of the Sicilian Clan.- Applications of Group Decision and Negotiations Analyzing Conflicts of Implementing High-speed Railway Project in Central Asia using Graph Model.- Strategic Negotiation for Resolving Infrastructure Development Disputes in the Belt and Road Initiative.- Attitudinal Analysis of Russia-Turkey Conflict with Chinese Role as a Third-Party Intervention.- Behavioral Modeling of Attackers Based on Prospect Theory and Corresponding Defenders Strategy.- A Multi-Stakeholder Approach to Energy Transition Policy Formation in Jordan.
Автор: Charu C. Aggarwal Название: Managing and Mining Uncertain Data ISBN: 1441935177 ISBN-13(EAN): 9781441935175 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This collection of surveys presents the most recent models, algorithms and applications in mining uncertain data. Organized to make it more accessible to applications-driven practitioners, it includes case studies based on real-world examples.
Автор: Pan Jeff Z., Vetere Guido, Gomez-Perez Jose Manuel Название: Exploiting Linked Data and Knowledge Graphs in Large Organisations ISBN: 3319833391 ISBN-13(EAN): 9783319833392 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Part I Knowledge Graph Foundations & Architecture.- Part II Constructing, Understanding and Consuming Knowledge Graphs.- Part III Industrial Applications and Successful Stories.
Автор: Marieke van Erp; Sebastian Hellmann; John P. McCra Название: Knowledge Graphs and Language Technology ISBN: 3319687220 ISBN-13(EAN): 9783319687223 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the combined refereed proceedings of ISWC Satellite Wor shops KEKIand NLP&DBpedia 2016 which were held in conjunction with ISWC 2016 in Kobe, Japan, inOctober 2016.
Автор: M. Jorge Cardoso; Tal Arbel; Enzo Ferrante; Xavier Название: Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics ISBN: 3319676741 ISBN-13(EAN): 9783319676746 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.
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