الصفحة 3
الصفحة 3
Learning Classifier Systems ; 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
Constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.
Large scale management of distributed systems ; 17th IFIP/IEEE International Workshop on distributed systems: operations and management, DSOM 2006, Dublin, Ireland, October 23-25, 2006, Proceedings
Presents the proceedings of the 17 IFIP/IEEE International Workshop on Distributed Systems : Operations and Management (DSOM 2006), which was held rd th in Dublin, Ireland during October 23 to 25 , 2006. In line with its reputation as one of the pre-eminent fora for the discussion and debate of advances of distributed systems management, the 2006 iteration of DSOM brought together an international audience of researchers and practitioners from both industry and academia. th DSOM 2006 was the 17 in a series of annual workshops, and it followed the footsteps of highly successful previous meetings, the most recent of which were held in Barcelona, Spain (DSOM 2005), Davis, USA (DSOM 2004), Heidelberg, Germany (DSOM 2003), Montreal, Canada (DSOM 2002) and Nancy, France (DSOM 2001). The goal of the DSOM workshops is to bring together researchers in the areas of networks, systems and services management, from both industry and academia, to discuss recent advances and foster future growth in these ?elds. In contrast to the larger management symposia, such as Integrated Management (IM) and Network Operations and Management (NOMS), the DSOM workshops are organised as sing- track programmes in order to stimulate interaction among participants.
Knowledge-Driven Computing : Knowledge Engineering and Intelligent Computations
Knowledge-Driven Computing constitutes an emerging area of intensive research located at the intersection of Computational Intelligence and Knowledge Engineering with strong mathematical foundations. It embraces methods and approaches coming from diverse computational paradigms, such as evolutionary computation and nature-inspired algorithms, logic programming and constraint programming, rule-based systems, fuzzy sets and many others. The use of various knowledge representation formalisms and knowledge processing and computing paradigms is oriented towards the efficient resolution of computationally complex and difficult problems.
Knowledge-Based Intelligent Information and Engineering Systems ; Vol.3682 : 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part II
The KES conference series has been established for almost a decade, and it cont- ues each year to attract participants from all geographical areas of the world, including Europe, the Americas, Australasia and the Paci?c Rim. The KES conferences cover a wide range of intelligent systems topics. The broad focus of the conference series is the theory and applications of intelligent systems. rom a pure research ?eld, intel- gent systems have advanced to the point where their abilities have been incorporated into many business and engineering...
Knowledge science, engineering and management; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I
Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.
Knowledge science, engineering and management ; 2nd International Conference, KSEM 2007, Melbourne, Australia, November 28-30, 2007, Proceedings
Constitutes the refereed proceedings of the Second International Conference on Knowledge Science, Engineering and Management, KSEM 2007, held in Melbourne, Australia, in November 2007. The papers provide new ideas and report research results in the broad areas of knowledge science, knowledge engineering, and knowledge management.
Knowledge science, engineering and management ; 1st International Conference, KSEM 2006, Guilin, China, August 5-8, 2006, Proceedings
Here are the refereed proceedings of the First International Conference on Knowledge Science, Engineering and Management, KSEM 2006, held in Guilin, China in August 2006 in conjunction with PRICAI 2006. The book presents 51 revised full papers and 57 revised short papers together with 4 invited talks, reporting a wealth of new ideas and current research results in the broad areas of knowledge science, knowledge engineering, and knowledge management.
Knowledge science, engineering and management ; 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part II
Constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning.
Knowledge Representation Techniques : A Rough Set Approach
The basis for the material in this book centers around a long term research project with autonomous unmanned aerial vehicle systems. One of the main research topics in the project is knowledge representation and reasoning. The focus of the research has been on the development of tractable combinations of approximate and nonmonotonic reasoning systems. The techniques developed are based on intuitions from rough set theory. Efforts have been made to take theory into practice by instantiating research results in the context of traditional relational database or deductive database systems.
Knowledge Representation and the Semantics of Natural Language
This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.
Knowledge Engineering : Practice and Patterns ; 16th International Conference, EKAW 2008, Acitrezza, Italy, September 29 - October 2, 2008. Proceedings
Constitutes the refereed proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008, held in Acitrezza, Sicily, Italy, in September/October 2008.The 17 revised full papers and 15 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on knowledge patterns and knowledge representation, matching ontologies and data integration, natural language, knowledge acquisition and annotations, search, query and interaction, as well as ontologies.
Knowledge and Information Visualization : Searching for Synergies
The basic ideas underlying knowledge visualization and information vi- alization are outlined. In a short preview of the contributions of this volume, the idea behind each approach and its contribution to the goals of the book are outlined. 2 The Basic Concepts of the Book Three basic concepts are the focus of this book: "data", "information", and "kno- edge". There have been numerous attempts to define the terms "data", "information", and "knowledge", among them, the OTEC Homepage "Data, Information, Kno- edge, and Wisdom" (Bellinger, Castro, & Mills, see http://www.syste- thinking.org/dikw/dikw.htm): Data are raw. They are symbols or isolated and non-interpreted facts. Data rep- sent a fact or statement of event without any relation to other data. Data simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself.
KI 2008 : Advances in Artificial Intelligence ; 31st Annual German Conference on AI, KI 2008, Kaiserslautern, Germany, September 23-26, 2008. Proceedings
This book constitutes the thoroughly refereed proceedings of the 31th Annual German Conference on Artificial Intelligence, KI 2008, held in Kaiserslautern, Germany, September 2008.The 15 revised full papers presented together with 2 invited contributions and 30 posters were carefully reviewed and selected from 77 submissions. The papers cover important areas such as pattern recognition, multi-agent systems, machine learning, natural language processing, constraint reasoning, knowledge representation and management, planning, and temporal reasoning.
KI 2005 : Advances in Artificial Intelligence ; 28th Annual German Conference on AI, KI 2005, Koblenz, Germany, September 11-14, 2005, Proceedings
Constitutes the refereed proceedings of the 28th Annual German Conference on Artificial Intelligence, KI 2005, held in Germany. This work presents papers organized in topical sections on knowledge representation and reasoning, machine learning, diagnosis, neural networks, planning, robotics, and cognitive modeling, philosophy, natural language.
Journal on Data Semantics XI
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics X
Web semantics and semi-structured data , Semantic caching , Data warehousing and semantic data mining , Spatial, temporal, multimedia and multimodal semantics , Semantics in data visualization , Semantic services for mobile users , Supporting tools , Applications of semantic-driven approaches These topics are to be understood as specifically related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not from the topics in the list. While the physical appearance of the journal issues is like the books from the we- known Springer LNCS series, the mode of operation is that of a journal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board.
Journal on Data Semantics VIII
Springer's LNCS Journal on Data Semantics aims at providing a highly visible dissemination channel for most remarkable work that in one way or another addresses research and development on issues related to the semantics of data. The target domain ranges from theories supporting the formal definition of semantic content to innovative domain-specific application of semantic knowledge. This publication channel should be of the highest interest to researchers and advanced practitioners working on the Semantic Web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics VII
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Journal on Data Semantics VI
Data warehousing and semantic data mining • Spatial, temporal, multimedia and multimodal semantics • Semantics in data visualization • Semantic services for mobile users • Supporting tools • Applications of semantic-driven approaches These topics are to be understood as speci?cally related to semantic issues. Contributions submitted to the journal and dealing with semantics of data will be considered even if they are not within the topics in the list. While the physical appearanceof the journal issues looks like the books from the well-known Springer LNCS series, the mode of operation is that of a jo- nal. Contributions can be freely submitted by authors and are reviewed by the Editorial Board. Contributions may also be invited, and nevertheless carefully reviewed, as in the case for issues that contain extended versions of best papers from major conferences addressing data semantics issues. Special issues, foc- ing on a speci?c topic, are coordinated by guest editors once the proposal for a special issue is accepted by the Editorial Board.
Journal on Data Semantics V
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
