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21 produkter
21 produkter
1 103 kr
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Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
1 103 kr
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Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
1 103 kr
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Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, and the trustworthy, dependable, repeatable, operable and explainable capabilities of data mining algorithms, tools and outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies and techniques, which are critical issues faced by data mining, as well as the ?ndings, thoughts and lessons learned in conducting several large-scale real-world data mining bu- ness applications.The aim and objective of domain driven data mining is to study effective and ef?cient methodologies, techniques, tools, and applications that can discover and deliver actionable knowledge that can be passed on to business people for direct decision-making and action-taking.
1 103 kr
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This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques.
1 103 kr
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Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, and the trustworthy, dependable, repeatable, operable and explainable capabilities of data mining algorithms, tools and outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies and techniques, which are critical issues faced by data mining, as well as the ?ndings, thoughts and lessons learned in conducting several large-scale real-world data mining bu- ness applications.The aim and objective of domain driven data mining is to study effective and ef?cient methodologies, techniques, tools, and applications that can discover and deliver actionable knowledge that can be passed on to business people for direct decision-making and action-taking.
Post-Mining of Association Rules
Techniques for Effective Knowledge Extraction
Inbunden, Engelska, 2009
2 490 kr
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1 103 kr
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The Web has emerged as a large, distributed data repository, & information on the Internet & in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. Knowledge Discovery in Multiple Databases provides a comprehensive introduction to the latest advancements in multi-database mining, & presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, & efficient algorithms for pattern discovery from multiple databases are described. This book is suitable for researchers, professionals & students in data mining, distributed data analysis, and machine learning. It is also appropriate for use as a text supplement for broader courses involving knowledge discovery in databases & data mining.
Del 8335 - Lecture Notes in Computer Science
Intelligent Strategies for Pathway Mining
Model and Pattern Identification
Häftad, Engelska, 2014
555 kr
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Chapter 1 presents an introduction to signaling pathway, including motivations, background knowledge and relevant data mining techniques for pathway data analysis. Chapter 2 presents a variety of data sources and data analysis with respect to signaling pathway, including data integration and relevant data mining applications.
Del 9208 - Lecture Notes in Computer Science
Data Science
Second International Conference, ICDS 2015, Sydney, Australia, August 8-9, 2015, Proceedings
Häftad, Engelska, 2015
533 kr
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This book constitutes the refereed proceedings of theSecond International Conference on Data Science, ICDS 2015, held in Sydney,Australia, during August 8-9, 2015. The 19 revised full papers and 5 short papers presentedwere carefully reviewed and selected from 31 submissions. data quality and data preparation;
Agent-Based Hybrid Intelligent Systems
An Agent-Based Framework for Complex Problem Solving
Häftad, Engelska, 2004
829 kr
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Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems.This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.
Advances in Knowledge Discovery and Data Mining
8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004, Proceedings
Häftad, Engelska, 2004
1 103 kr
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This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004.The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.
PRICAI 2004: Trends in Artificial Intelligence
8th Pacific Rim International Conference on Artificial Intelligence, Auckland, New Zealand, August 9-13, 2004, Proceedings
Häftad, Engelska, 2004
1 103 kr
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This book constitutes the refereed proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2004, held in Auckland, New Zealand in August 2004. The 94 revised full papers and 45 revised poster papers presented together with 3 invited contributions were carefully reviewed and selected from 356 submissions. The papers are organized in topical sections on logic and reasoning, knowledge representation and search, ontologies, planning, constraint satisfaction, machine learning, computational learning, Bayesian networks, evolutionary computing, neural networks, fuzzy logic, data mining, classification and clustering, case-based reasoning, information retrieval, agent technology, robotics, bioinformatics, image processing and computer vision, natural language processing, and speech understanding and interaction.
555 kr
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Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention.The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.
Distributed Artificial Intelligence: Architecture and Modelling
First Australian Workshop on DAI, Canberra, ACT, Australia, November 13, 1995. Proceedings
Häftad, Engelska, 1996
555 kr
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This book constitutes the refereed proceedings of the First Australian Workshop on Distributed Artificial Intelligence, held in Canberra, ACT, Australia, in November 1995.The 16 full papers included in the book are revised versions of the contributions accepted for presentation at the workshop; they cover a wide range of current issues in the field of DAI, such as formal frameworks, methodology, theory, and architecture; various aspects of agents and multi-agent systems are addressed.
Multi-Agent Systems Methodologies and Applications
Second Australian Workshop on Distributed Artificial Intelligence, Cairns, QLD, Australia, August 27, 1996, Selected Papers
Häftad, Engelska, 1997
555 kr
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This book constitutes the strictly refereed post-workshop proceedings originating from the Second Australian Workshop on Distributed Artificial Intelligence, held in Cairns, QLD, Australia, in August 1996, as a satellite meeting of PRICAI'96.The 13 revised full papers presented have been selected for inclusion in the book during a very careful and iterated process of reviewing and improvement. Among these papers are three invited ones, by leading scientists, solicited in order to round off the overall presentation and coverage of relevant topics. A wide range of multi-agent systems issues is covered including methodologies, cooperation, conflict resolution, applications, mobility, adaptation, negotiation, and implementations.
555 kr
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This book constitutes the thoroughly refereed post-workshop proceedings of three workshops held in conjunction with the 10th Australian Joint Conference on Artificial Intelligence in Perth, Australia, in December 1997.The 17 revised full papers presented were carefully reviewed for inclusion in the book. The book is divided into sections on formal methods of agency, reasoning agents, communication and coordination, social interaction, and practical issues for distributed artificial intelligence systems.
Multi-Agent Systems. Theories, Languages and Applications
4th Australian Workshop on Distributed Artificial Intelligence, Brisbane, QLD, Australia, July 13, 1998, Proceedings
Häftad, Engelska, 1998
555 kr
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This volume contains revisedversions of selected papers presented at the Fourth Australian Workshop on Distributed Arti?cial Intelligence (DAK'91), together with a set of invited papers. Each paper has been reviewed by at least two program committee members. The workshop was held in Brisbane, Queensland, Australia on July 17,1992. The goalof the workshopwas to promoteresearchin distributed arti?cial intelligence and multi-agent systems, both nationally and internationally. Thepapers covera widerangeofissuesin the?eldof distributed arti?cial intelligence and multi-agent systems, such as theories, languages, and applications. Manypeoplecontributedtothesuccessofthis workshop. Wewouldliketothank all the authors who submitted papers to the workshop. Many thanks also to the members of the programme committee who diligently reviewed all the papers submitted. Finally, we thank the editorial sta? of Springer-Verlag for publishing this contribution to the Lecture Notes in Arti?cial Intelligence series. October 1998 Chengqi Zhang and Dickson Lukose Programme Committee Chengqi Zhang (Co-Chair) University of New England, Australia Dickson Lukose (Co-Chair) Brightware Inc., USA Victor Lesser University of Massachusetts, USA Je?rey S. Rosenschein Hebrew University, Israel Toshiharu Sugawara NTT Basic Research Labs, Japan Rose Dieng ACACIA Project, INRIA, France Norbert Glaser CRIN-INRIA Lorraine, France Sascha Ossowski Rey Juan Carlos Univ, Spain Michael Luck University of Warwick, UK Mark d'Inverno University of Westminster, UK Tim Norman University of London, UK Douglas Norrie University of Calgary, Canada Bernard Moulin Laval University, Canada Zhisheng Huang University of London, UK Minjie Zhang Edith Cowan University, Australia Brahim Chaib-draa Laval University, Canada Table of Contents TeamFormationbySelf-InterestedMobileAgents ...
Approaches to Intelligent Agents
Second Pacific Rim International Workshop on Multi-Agents, PRIMA'99, Kyoto, Japan, December 2-3, 1999 Proceedings
Häftad, Engelska, 1999
555 kr
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This book constitutes the refereed proceedings of the Second Pacific Rim International Workshop on Multi-Agents, PRIMA'99, held in Kyoto, Japan in December 1999. The 17 revised full papers presented were carefully reviewed and selected from a total of 43 submissions. The papers are organized in sections on agent cooperation, agent mobility, learning in multiagent systems, interface agents, and agent system design.
Autonomous Intelligent Systems: Multi-Agents and Data Mining
Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings
Häftad, Engelska, 2007
555 kr
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Since early 1990, multi-agent systems (MAS), data mining, and knowledge d- covery (KDD) have remained areas of high interest in the research and - velopment of intelligent information technologies. Indeed, MAS o?ers powerful metaphors for information system conceptualization, a range of new techniques, and technologies speci?cally focused on the design and implementation of lar- scale open distributed intelligent systems. KDD also provides intelligent inf- mation technology with powerful ideas, algorithms, and software means to help cope with the main problem of arti?cial intelligence, formulated in the we- known question “Where does the knowledge come from?”, thus actually making modern applications intelligent and adaptive. The evident recent trend in both science and industry is to integrate and take advantage of both technologies. The existing experience with combined application of multi-agent technology to design architectures of distributed (- erarchical and peer-to-peer) data mining and KDD systems, as well as the u- lization of data mining and KDD achievements to provide enhanced intelligence of MAS, con?rms the fact that both technologies are capable of mutual enri- ment and their integrateduse may result in intelligent information systems with new emergent properties. The 1st International Workshop “Autonomous Int- ligent Systems: Agents and Data Mining” (AIS-ADM 2005, June 6–8, 2005, St. Petersburg, Russia) was a response to the aforementioned trend. It con?rmed the interest of academic and industry communities in advancing the e?orts to integrate achievements in MAS and KDD, thus resulting in a new dimension and further progress in intelligent information technology.
555 kr
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The application of formal methods to security protocol analysis has attracted increasing attention in the past two decades, and recently has been sh- ing signs of new maturity and consolidation. The development of these formal methodsismotivatedbythehostilenatureofsomeaspectsofthenetworkand the persistent e?orts of intruders, and has been widely discussed among - searchers in this ?eld. Contributions to the investigation of novel and e?cient ideas and techniques have been made through some important conferences and journals, such asESORICS,CSFW andACM Transactions in Computer Systems. Thus, formal methods have played an important role in a variety of applications such as discrete system analysis for cryptographic protocols, - lief logics and state exploration tools. A complicated security protocol can be abstractedasamanipulationofsymbolsandstructurescomposedbysymbols. The analysis of e-commerce (electronic commerce) protocols is a particular case of such symbol systems. There have been considerable e?orts in developing a number of tools for ensuring the security of protocols, both specialized and general-purpose, such as belief logic and process algebras. The application of formal methods starts with the analysis of key-distribution protocols for communication between two principals at an early stage. With the performance of transactions - coming more and more dependent on computer networks, and cryptography becoming more widely deployed, the type of application becomes more varied and complicated. The emerging complex network-based transactions such as ?nancial transactionsand secure groupcommunication have not only brought innovationstothecurrentbusinesspractice,butthey alsoposeabigchallenge to protect the information transmitted over the open network frommalicious attacks.
163 kr
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