Data Mining And Knowledge Discovery Via Logic Based Methods

✏Book Title : Data Mining and Knowledge Discovery via Logic Based Methods
✏Author : Evangelos Triantaphyllou
✏Publisher : Springer Science & Business Media
✏Release Date : 2010-06-08
✏Pages : 350
✏ISBN : 9781441916303
✏Available Language : English, Spanish, And French

✏Data Mining and Knowledge Discovery via Logic Based Methods Book Summary : The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.

✏Book Title : Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques
✏Author : Evangelos Triantaphyllou
✏Publisher : Springer Science & Business Media
✏Release Date : 2006-09-10
✏Pages : 748
✏ISBN : 9780387342962
✏Available Language : English, Spanish, And French

✏Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques Book Summary : This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.

✏Book Title : Data Mining and Knowledge Discovery Handbook
✏Author : Oded Maimon
✏Publisher : Springer Science & Business Media
✏Release Date : 2006-05-28
✏Pages : 1383
✏ISBN : 9780387254654
✏Available Language : English, Spanish, And French

✏Data Mining and Knowledge Discovery Handbook Book Summary : Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

✏Book Title : Principles of Data Mining and Knowledge Discovery
✏Author : Djamel A. Zighed
✏Publisher : Springer
✏Release Date : 2003-07-31
✏Pages : 701
✏ISBN : 9783540453727
✏Available Language : English, Spanish, And French

✏Principles of Data Mining and Knowledge Discovery Book Summary : This book constitutes the refereed proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000, held in Lyon, France in September 2000. The 86 revised papers included in the book correspond to the 29 oral presentations and 57 posters presented at the conference. They were carefully reviewed and selected from 147 submissions. The book offers topical sections on new directions, rules and trees, databases and reward-based learning, classification, association rules and exceptions, instance-based discovery, clustering, and time series analysis.

✏Book Title : Principles of Data Mining and Knowledge Discovery
✏Author : Djamel A. Zighed
✏Publisher : Springer Science & Business Media
✏Release Date : 2000-09-06
✏Pages : 701
✏ISBN : 9783540410669
✏Available Language : English, Spanish, And French

✏Principles of Data Mining and Knowledge Discovery Book Summary : This book constitutes the refereed proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000, held in Lyon, France in September 2000. The 86 revised papers included in the book correspond to the 29 oral presentations and 57 posters presented at the conference. They were carefully reviewed and selected from 147 submissions. The book offers topical sections on new directions, rules and trees, databases and reward-based learning, classification, association rules and exceptions, instance-based discovery, clustering, and time series analysis.

✏Book Title : Methodologies for Knowledge Discovery and Data Mining
✏Author : Ning Zhong
✏Publisher : Springer
✏Release Date : 2003-06-29
✏Pages : 540
✏ISBN : 9783540489122
✏Available Language : English, Spanish, And French

✏Methodologies for Knowledge Discovery and Data Mining Book Summary : This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.

✏Book Title : Soft Computing for Knowledge Discovery and Data Mining
✏Author : Oded Maimon
✏Publisher : Springer Science & Business Media
✏Release Date : 2007-10-25
✏Pages : 433
✏ISBN : 9780387699356
✏Available Language : English, Spanish, And French

✏Soft Computing for Knowledge Discovery and Data Mining Book Summary : Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

✏Book Title : Principles of Data Mining and Knowledge Discovery
✏Author : Jan Komorowski
✏Publisher : Springer Science & Business Media
✏Release Date : 1997-06-13
✏Pages : 396
✏ISBN : 3540632239
✏Available Language : English, Spanish, And French

✏Principles of Data Mining and Knowledge Discovery Book Summary : This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997. The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.

✏Book Title : Foundations of Data Mining and Knowledge Discovery
✏Author : Tsau Young Lin
✏Publisher : Springer Science & Business Media
✏Release Date : 2005-09-02
✏Pages : 378
✏ISBN : 3540262571
✏Available Language : English, Spanish, And French

✏Foundations of Data Mining and Knowledge Discovery Book Summary : "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.

✏Book Title : Advanced Methods for Knowledge Discovery from Complex Data
✏Author : Ujjwal Maulik
✏Publisher : Springer Science & Business Media
✏Release Date : 2006-03-30
✏Pages : 369
✏ISBN : 9781846282843
✏Available Language : English, Spanish, And French

✏Advanced Methods for Knowledge Discovery from Complex Data Book Summary : The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.