Автор: Liu Zhiyuan, Lin Yankai, Sun Maosong Название: Representation Learning for Natural Language Processing ISBN: 9811555753 ISBN-13(EAN): 9789811555756 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Liu Zhiyuan, Lin Yankai, Sun Maosong Название: Representation Learning for Natural Language Processing ISBN: 9811555729 ISBN-13(EAN): 9789811555725 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Поставка под заказ.
Описание: The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI.
The book is split into three volumes:- the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning)- the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms)- the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3.
Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries.
Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty.
Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
Описание: This volume presents a panorama of the diverse activities organized by V. Heiermann and D. Prasad in Marseille at the CIRM for the Chaire Morlet event during the first semester of 2016. It assembles together expository articles on topics which previously could only be found in research papers.Starting with a very detailed article by P. Baumann and S. Riche on the geometric Satake correspondence, the book continues with three introductory articles on distinguished representations due to P. Broussous, F. Murnaghan, and O. Offen; an expository article of I. Badulescu on the Jacquet–Langlands correspondence; a paper of J. Arthur on functoriality and the trace formula in the context of 'Beyond Endoscopy', taken from the Simons Proceedings; an article of W-W. Li attempting to generalize Godement–Jacquet theory; and a research paper of C. Moeglin and D. Renard, applying the trace formula to the local Langlands classification for classical groups.The book should be of interest to students as well as professional researchers working in the broad area of number theory and representation theory.
Автор: Arjen Hommersom; Peter J.F. Lucas Название: Foundations of Biomedical Knowledge Representation ISBN: 3319280066 ISBN-13(EAN): 9783319280066 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
How to Read the Book "Foundations of Biomedical Knowledge Representation".- An Introduction to Knowledge Representation and Reasoning in Healthcare.- Representing Knowledge for Clinical Diagnostic Reasoning.- Automated Diagnosis of Breast Cancer on Medical.- Monitoring in the Healthcare Setting.- Conformance Verification of Clinical Guidelines in Presence of Computerized and Human-Enhanced.- Modelling and Monitoring the Individual Patient in Real Time.- Personalised Medicine: Taking a New Look at the Patient.- Graphical Modelling in Genetics and Systems Biology.- Chain Graphs and Gene Networks.- Prediction and Prognosis of Health and Disease.- Trajectories Through the Disease Process: Cross Sectional and Longitudinal Studies.- Dynamic Bayesian Network for Cervical Cancer Screening.- Modeling Dynamic Processes with Memory by Higher Order Temporal Models.- Treatment of Disease: The Role of Knowledge Representation for Treatment Selection.- Predicting Adverse Drug Events from Electronic Medical Records.- User Modelling for Patient Tailored Virtual Rehabilitation.- Supporting Physicians and Patients through Recommendation: Guidelines and Beyond.- A Hybrid Approach to the Verification of Computer Interpretable Guidelines.- Aggregation of Clinical Evidence Using Argumentation.
Описание: This Festschrift is published in honor of Gerhard Brewka on the occasion of his 60th birthday and contains articles from fields reflecting the breadth of Gerd`s work.
Автор: Ashok K Goel; Mateja Jamnik; N Hari Narayanan Название: Diagrammatic Representation and Inference ISBN: 364214599X ISBN-13(EAN): 9783642145995 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 6th International Conference on Theory and Application of Diagrams, Diagrams 2010, held in Portland, OR, USA, in August 2010.
Автор: Haemmerl? Название: Graph-Based Representation and Reasoning ISBN: 3319409840 ISBN-13(EAN): 9783319409849 Издательство: Springer Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 22th International Conference on Conceptual Structures, ICCS 2016, held in Annecy, France, in July 2016. The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 40 submissions.
Автор: Michel Chein; Marie-Laure Mugnier Название: Graph-based Knowledge Representation ISBN: 1849967695 ISBN-13(EAN): 9781849967693 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In addressing the question of how far it is possible to go in knowledge representation and reasoning through graphs, the authors cover basic conceptual graphs, computational aspects, and kernel extensions. The basic mathematical notions are summarized.
Formal specifications are an important tool for the construction, verification and analysis of systems, since without it is hardly possible to explain whether a system worked correctly or showed an expected behavior. This book proposes the use of representation theorems as a means to develop an understanding of all models of a specification in order to exclude possible unintended models, demonstrating the general methodology with representation theorems for applications in qualitative spatial reasoning, data stream processing, and belief revision.
For qualitative spatial reasoning, it develops a model of spatial relatedness that captures the scaling context with hierarchical partitions of a spatial domain, and axiomatically characterizes the resulting relations. It also shows that various important properties of stream processing, such as prefix-determinedness or various factorization properties can be axiomatized, and that the axioms are fulfilled by natural classes of stream functions. The third example is belief revision, which is concerned with the revision of knowledge bases under new, potentially incompatible information. In this context, the book considers a subclass of revision operators, namely the class of reinterpretation operators, and characterizes them axiomatically. A characteristic property of reinterpretation operators is that of dissolving potential inconsistencies by reinterpreting symbols of the knowledge base.
Intended for researchers in theoretical computer science or one of the above application domains, the book presents results that demonstrate the use of representation theorems for the design and evaluation of formal specifications, and provide the basis for future application-development kits that support application designers with automatically built representations.
Описание: This book constitutes the refereed proceedings of the 13th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2017, held in Ustron, Poland, in May/June 2017.It consists of 44 carefully reviewed papers selected from 118 submissions.
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