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The Modern Algebra of Information Retrieval
This book takes a unique approach to information retrieval by laying down the foundations for a modern algebra of information retrieval based on lattice theory. All major retrieval methods developed so far are described in detail ئ Boolean, Vector Space and probabilistic methods, but also Web retrieval algorithms like PageRank, HITS, and SALSA ئ and the author shows that they all can be treated elegantly in a unified formal way, using lattice theory as the one basic concept. Further, he also demonstrates that the lattice-based approach to information retrieval allows us to formulate new retrieval methods. Sándor Dominichѫs presentation is characterized by an engineering-like approach, describing all methods and technologies with as much mathematics as needed for clarity and exactness.
Symbolic and quantitative approaches to reasoning with uncertainty ; 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007, Proceedings
Coverage in the 78 revised full papers, presented together with three invited papers, includes Bayesian networks, graphical models, learning causal networks, planning, causality and independence, preference modeling and decision, argumentation systems, inconsistency handling, and uncertainty measures.
Structural, Syntactic, and Statistical Pattern Recognition ; Joint IAPR International Workshops, SSPR 2006 and SPR 2006, Hong Kong, China, August 17-19, 2006, Proceedings
This book constitutes the refereed proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held jointly in Hong Kong, China in August 2006 as a satellite event of the 18th International Conference of Pattern Recognition, ICPR 2006. The 38 revised full papers and 61 revised poster papers presented together with 4 invited papers were carefully reviewed and selected from 217 submissions. The papers are organized in topical sections on image analysis, vision, character recognition, bayesian networks, graph-based methods, similarity and feature extraction, image and video, vision, kernel-based methods, recognition and classification, similarity.
Structural, Syntactic, and Statistical Pattern Recognition ; Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings
This book includes : graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.
Soft Computing Applications in Business
Soft computing techniques are widely used in most businesses. This book consists of several important papers on the applications of soft computing techniques for the business field.The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer theory, ensemble learning, evolutionary programming, fuzzy decision trees, hidden Markov models, intelligent agents, k-means clustering, maximum likelihood Hebbian learning, neural networks, opportunistic scheduling, probability distributions combined with Monte Carlo methods, rough sets, self organizing maps, support vector machines, uncertain reasoning, other statistical and machine learning techniques, and combinations of these techniques.
Scalable Uncertainty Management ; 2nd International Conference, SUM 2008, Naples, Italy, October 1-3, 2008. Proceedings
The book address artificial intelligence researchers, database researchers, and practitioners to demonstrate theoretical techniques required to manage the uncertainty that arises in large scale real world applications and to cope with large volumes of uncertainty and inconsistency in databases, the Web, the semantic Web, and artificial intelligence in general.
Scalable Uncertainty Management ; 1st International Conference, SUM 2007, Washington, DC, USA, October 10-12, 2007, Proceeding
This book constitutes the refereed proceedings of the First International Conference on Scalable Uncertainty Management, SUM 2007, held in Washington, DC, USA, in October 2007. The papers address artificial intelligence researchers, database researchers and practitioners.
Recent Advances in Intrusion Detection ; 11th International Symposium, RAID 2008, Cambridge, MA, USA, September 15-17, 2008. Proceedings
This book is organized in topical sections on rootkit prevention, malware detection and prevention, high performance intrusion and evasion, Web application testing and evasion, alert correlation and worm detection, as well as anomaly detection and network traffic analysis.
Probabilistic Modeling in Bioinformatics and Medical Informatics
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.
Probabilistic Inductive Logic Programming : Theory and Applications
One of the key open questions within arti?cial intelligence is how to combine probability and logic with learning. This question is getting an increased tentioninseveral disciplines suchas knowledg erepresentation, reasoningabout uncertainty, data mining, and machine learning simulateously,This book providesan introduction to this ?eld with an emphasison those methods based on logic programming principles. The book is also the main result of the successful European ISTFET projectno.FP6-508861on Applition of ProbabilisticInductive Logic Programming (APRILII,2004-2007).It was concerned with theory, implementation sand applications of probabilisticinductivelogic programming.
Multiple Classifier Systems ; 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings
These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic.
Innovations in Bayesian Networks : Theory and Applications
Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field.
Inductive logic programming ; 18th International Conference, ILP 2008 Prague, Czech Republic, September 10-12, 2008 Proceedings
This book constitutes the refereed proceedings of the 18th International Conference on Inductive Logic Programming, ILP 2008, held in Prague, Czech Republic, in September 2008.The 20 revised full papers presented together with the abstracts of 5 invited lectures were carefully reviewed and selected during two rounds of reviewing and improvement from 46 initial submissions. All current topics in inductive logic programming are covered, ranging from theoretical and methodological issues to advanced applications. The papers present original results in the first-order logic representation framework, explore novel logic induction frameworks, and address also new areas such as statistical relational learning, graph mining, or the semantic Web.
Inductive logic programming ; 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 16th International Conference on Inductive Logic Programming, ILP 2006, held in Santiago de Compostela, Spain, in August 2006. The papers address all current topics in inductive logic programming, ranging from theoretical and methodological issues to advanced applications.
Inductive logic programming ; 15th International Conference, ILP 2005, Bonn, Germany, August 10-13, 2005, Proceedings
“Change is inevitable.” Embracing this quote we have tried to carefully exp- iment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd Inter- tional Conference on Machine Learning, and also in close proximity to IJCAI 2005, the 19th International Joint Conference on Arti?cial Intelligence. - location can be tricky, but we greatly bene?ted from the local support provided by Codrina Lauth, Michael May, and others. We were also able to invite all ILP and ICML participants to shared events including a poster session, an invited talk, and a tutorial about the exciting new area of “statistical relational lea- ing”. Two more invited talks were exclusively given to ILP participants and were presented as a kind of stock-taking—?ttingly so for the 15th event in a series—but also tried to provide a recipe for future endeavours.
Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope.
Fundamental approaches to software engineering ; 11th International Conference, FASE 2008, Held as Part of the Joint European conferences on theory and practice of software, ETAPS 2008, Budapest, Hungary, March 29-April 6, 2008. Proceedings
The fve main conferences received 571 submissions, 147 of which were accepted, giving an overall acceptance rate of less than 26%, with each conference below 27%.Congratulationsthereforetoallthe authorswhomadeittothe alprogramme! I hope that most of the other authors will still have found a way of participating in this exciting event, and that you will all continue submitting to ETAPS and contributing to make of it the best conference in the area،The events that comprise ETAPS address various aspects of the system velopment process,including specifcation, design, implementation, analysis and improvement.
Fundamental approaches to software engineering ; 10th International Conference, FASE 2007 Held as part of the joint European conference on theory and practice of software, ETAPS 2007 Braga, Portugal, March 24 - April 1, 2007 Proceedings
This book constitutes the refereed proceedings of the 10th International Conference on Fundamental Approaches to Software Engineering, FASE 2007, held in Braga, Portugal in March/April 2007 as part of ETAPS 2007, the Joint European Conferences on Theory and Practice of Software.
Defence Applications of Multi-Agent Systems; International Workshop, DAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised and Invited Papers
This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2005, held in Utrecht, The Netherlands in July 2005 as an associated event of AAMAS 2005, the main international conference on autonomous agents and multi-agent systems. The 10 revised full papers presented together with 1 invited article are organized in topical sections on decision support and simulation, unmanned aerial vehicles, as well as on systems and security.
Data mining and Knowledge discovery handbook
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.
