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"To help readers build on familiar territory, Metapattern compares the metapattern approach with object-oriented analysis and modeling, offering metapattern alternatives that demonstrate its richness in providing context-oriented solutions. In addition, the author reviews major established design patterns in data modeling, analysis, and business process engineering, and shows how the metapattern provides a frame of reference for understanding, accommodating, and transcending these patterns. The author also provides powerful modeling heuristics that take into account plurality through the definition of context, and by doing so, bring consistency and uniformity to information systems."--BOOK JACKET.
Most of us suffer from a lack of self-confidence. Many of us avoid situations in which we lack confidence. But think of the things you could accomplish if you have more self-esteem and self-confidence. This book will show you: How to reframe your self-esteem so you can feel truly confident How performance anxiety can debilitate you and how to stop it How to tap in to past successful memories to increase your present self-confidence How to access self-confidence in any situation you want How your own self-talk can either make you consistently self-confident or focus you on failure One of America's foremost business psychologists, will give you concepts and applicable techniques using the newest NLP skills to increase your self-confidence.
The refereed proceedings of the 14th International Conference on Rewriting Techniques and Applications, RTA 2003, held in Valencia, Spain in June 2003. The 26 revised regular papers and 6 system descriptions presented together with 3 invited contributions were carefully reviewed and selected from 61 submissions. All current aspects of rewriting are addressed.
"This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals"--Provided by publisher.
Cybernetic pioneer Warren McCullough asked: "What is a man, that he may know a number; and what is a number, that a man may know it?" Thinking along much the same lines, my question here is: "What is a creative mind, that it might emerge from a complex system; and what is a complex system, that it might give rise to a creative mind?" Complexity science is a fashionable topic these days. My perspective on complexity, however, is a somewhat unusual one: I am interested in complex systems science principally as it reflects on abstract mathematical, computational models of mind. In my three previous books, The Structure of Intelligence, Evolving Mind, and Chaotic Logic, I have outlined a comprehensive complex-systems-theoretic theory of mind that I now call the psynet model. This book is a continuation of the research program presented in my previous books (and those books will be frequently referred to here, by the nicknames EM and CL). One might summarize the trajectory of thought spanning these four books as follows. SI formulated a philosophy and mathem- ics of mind, based on theoretical computer science and the concept of "pattern. " EM analyzed the theory of evolution by natural selection in similar terms, and used this computational theory of evolution to establish the evolutionary nature of thought.
In the interdisciplinary tradition of Buckminster Fuller's work, Gregory Bateson's Mind and Nature, and Fritjof Capra's Tao of Physics, Metapatterns embraces both nature and culture, seeking out the grand-scale patterns that help explain the functioning of our universe.
The study of patterns in the context of ontology engineering for the semantic web was pioneered more than a decade ago by Blomqvist, Sandkuhl and Gangemi. Since then, this line of research has flourished and led to the development of ontology design patterns, knowledge patterns, and linked data patterns: the patterns as they are known by ontology designers, knowledge engineers, and linked data publishers, respectively. A key characteristic of those patterns is that they are modular and reusable solutions to recurrent problems in ontology engineering and linked data publishing. This book contains recent contributions which advance the state of the art on theory and use of ontology design patterns. The papers collected in this book cover a range of topics, from a method to instantiate content patterns, a proposal on how to document a content pattern, to a number of patterns emerging in ontology modeling in various situations.
In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.
Examines every category of occult phenomena from ESP to Eastern ritual and explores the basic laws of magic, relating them to the natural laws of the universe.
Data mining from traditional relational databases as well as from non-traditional ones such as semi-structured data, Web data, and scientific databases housing biological, linguistic, and sensor data has recently become a popular way of discovering hidden knowledge. This book on database support for data mining is developed to approaches exploiting the available database technology, declarative data mining, intelligent querying, and associated issues, such as optimization, indexing, query processing, languages, and constraints. Attention is also paid to the solution of data preprocessing problems, such as data cleaning, discretization, and sampling. The 16 reviewed full papers presented were carefully selected from various workshops and conferences to provide complete and competent coverage of the core issues. Some papers were developed within an EC funded project on discovering knowledge with inductive queries.