Data Exploration Using Example-Based Methods, Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis
Автор: Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis Название: Data Exploration Using Example-Based Methods ISBN: 1681734559 ISBN-13(EAN): 9781681734552 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: Data usually comes in a plethora of formats and dimensions, rendering the information extraction and exploration processes challenging. Thus, being able to perform exploratory analyses of the data with the intent of having an immediate glimpse of some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicated declarative languages (such as SQL) and mechanisms, while at the same time retaining the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or analyst, circumvents query languages by using examples as input. An example is a representative of the intended results or, in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind but may not be able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when they are performing a particularly challenging task like finding duplicate items, or when they are simply exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how different data types require different techniques and present algorithms that are specifically designed for relational, textual, and graph data. The book also presents the challenges and new frontiers of machine learning in online settings that have recently attracted the attention of the database community. The book concludes with a vision for further research and applications in this area.
Автор: Tshilidzi Marwala Название: Condition Monitoring Using Computational Intelligence Methods ISBN: 1447161343 ISBN-13(EAN): 9781447161349 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows how condition monitoring can be used to help avoid equipment failure and lengthen useful life, minimize downtime and reduce maintenance costs. Covers the uses of such techniques as principal component analysis, and much more.
Автор: Bergmeir Название: Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data ISBN: 3658203668 ISBN-13(EAN): 9783658203665 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets.
Автор: Sean Xiang Zhou; Yong Rui; Thomas S. Huang Название: Exploration of Visual Data ISBN: 1461351065 ISBN-13(EAN): 9781461351061 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Exploration of Visual Data presents latest research efforts in the area of content-based exploration of image and video data. The main objective is to bridge the semantic gap between high-level concepts in the human mind and low-level features extractable by the machines.
The two key issues emphasized are "content-awareness" and "user-in-the-loop." The authors provide a comprehensive review on algorithms for visual feature extraction based on color, texture, shape, and structure, and techniques for incorporating such information to aid browsing, exploration, search, and streaming of image and video data. They also discuss issues related to the mixed use of textual and low-level visual features to facilitate more effective access of multimedia data.
To bridge the semantic gap, significant recent research efforts have also been put on learning during user interactions, which is also known as "relevance feedback." The difficulty and challenge also come from the personalized information need of each user and a small amount of feedbacks the machine could obtain through real-time user interaction. The authors present and discuss several recently proposed classification and learning techniques that are specifically designed for this problem, with kernel- and boosting-based approaches for nonlinear extensions.
Exploration of Visual Data provides state-of-the-art materials on the topics of content-based description of visual data, content-based low-bitrate video streaming, and latest asymmetric and nonlinear relevance feedback algorithms, which to date are unpublished.
Exploration of Visual Data will be of interest to researchers, practitioners, and graduate-level students in the areas of multimedia information systems, multimedia databases, computer vision, machine learning.
Автор: Walter J. Scheirer Название: Extreme Value Theory-Based Methods for Visual Recognition ISBN: 1627057005 ISBN-13(EAN): 9781627057004 Издательство: Turpin Рейтинг: Цена: 68930.00 T Наличие на складе: Невозможна поставка. Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Автор: Ian R. Petersen; Valery A. Ugrinovskii; Andrey V. Название: Robust Control Design Using H-? Methods ISBN: 1447111443 ISBN-13(EAN): 9781447111443 Издательство: Springer Рейтинг: Цена: 174150.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is a unified collection of important recent results for the design of robust controllers for uncertain systems, primarily based on H8 control theory or its stochastic counterpart, risk sensitive control theory. Two practical applications are used to illustrate the methods throughout.
Автор: Hans-Christian Hege; Konrad Polthier; Gerik Scheue Название: Topology-Based Methods in Visualization II ISBN: 3662502364 ISBN-13(EAN): 9783662502365 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book contains 13 peer-reviewed papers resulting from the second workshop on "Topology-Based Methods in Visualization", held 2007 in Grimma near Leipzig, Germany. It presents the state of the art of topology-based visualization research.
Автор: Tshilidzi Marwala Название: Economic Modeling Using Artificial Intelligence Methods ISBN: 1447150090 ISBN-13(EAN): 9781447150091 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies evolutionary computing to model evolving economic environments.
Автор: Garcia-Fidalgo Emilio, Ortiz Alberto Название: Methods for Appearance-Based Loop Closure Detection: Applications to Topological Mapping and Image Mosaicking ISBN: 3030093735 ISBN-13(EAN): 9783030093730 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Mapping and localization are two essential tasks in autonomous mobile robotics. Due to the unavoidable noise that sensors present, mapping algorithms usually rely on loop closure detection techniques, which entail the correct identification of previously seen places to reduce the uncertainty of the resulting maps. This book deals with the problem of generating topological maps of the environment using efficient appearance-based loop closure detection techniques. Since the quality of a visual loop closure detection algorithm is related to the image description method and its ability to index previously seen images, several methods for loop closure detection adopting different approaches are developed and assessed. Then, these methods are used in three novel topological mapping algorithms. The results obtained indicate that the solutions proposed attain a better performance than several state-of-the-art approaches. To conclude, given that loop closure detection is also a key component in other research areas, a multi-threaded image mosaicing algorithm is proposed. This approach makes use of one of the loop closure detection techniques previously introduced in order to find overlapping pairs between images and finally obtain seamless mosaics of different environments in a reasonable amount of time.
Автор: Claudia I. Gonzalez; Patricia Melin; Juan R. Castr Название: Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic ISBN: 3319539930 ISBN-13(EAN): 9783319539935 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preprocessing phase of a face rec-ognition system;
Автор: Tshilidzi Marwala Название: Economic Modeling Using Artificial Intelligence Methods ISBN: 1447159195 ISBN-13(EAN): 9781447159193 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies evolutionary computing to model evolving economic environments.
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