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Making Globally Distributed Software Development a Success Story : International Conference on Software Process, ICSP 2008 Leipzig, Germany, May 10-11, 2008 Proceedings
This volume contains papers presented at the International Conference on Software Process (ICSP 2008) held in Leipzig, Germany, during May 10-11, 2008. ICSP 2008 was the second conference of the ICSP series. The theme of ICSP 2008 was “Making Globally Distributed Software Development a Success Story. ” Software developers work in a dynamic context of frequently changing technologies and with limited resources. Globally distributed development teams are under ev- increasing pressure to deliver their products more quickly and with higher levels of qu- ity. At the same time, global competition is forcing software development organizations to cut costs by rationalizing processes, outsourcing part of or all development activities, reusing existing software in new or modified applications, and evolving existing systems to meet new needs, while still minimizing the risk of projects failing to deliver.
Machine learning, image processing, network security and data sciences ; 2nd International conference, MIND 2020, Silchar, India, July 30 - 31, 2020, Proceedings, Part I
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II
Constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.
Machine Learning and Data Mining in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Machine Learning : Modeling Data Locally and Globally
Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications.
Logic, Language, and Computation ; 6th International Tbilisi Symposium on Logic, Language, and Computation. Batumi, Georgia, September 12-16, 2005, Revised Selected Papers
Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book constitutes the second volume of the FoLLI LNAI subline. It represents the thoroughly refereed post-proceedings of the 6th International Tbilisi Symposium on Logic, Language, and Computation, TbiLLC 2005, held in Batumi, Georgia, in September 2005.
Leveraging the Semantics of Topics Maps ; 2nd International Conference on Topic Maps Research and Applications, TMRA 2006, Leipzig, Germany, October 11-12, 2006, Revised Selected papers
The papers in this volume were presented at TMRA 2006, the International Conference on Topic Maps Research and Applications, held October 11–12, 2006, in Leipzig, Germany. TMRA 2006 was the second conference of an annual series of international conferences dedicated to Topic Maps in research and industry.
Law and the Semantic Web : Legal Ontologies, Methodologies, Legal Information Retrieval, and Applications
As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens — at some points in their lives — have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important because it that can improve citizens’ interaction with law, as well as improve legal professionals’ work environment. Legal professionals dedicate a significant amount of their time to finding, reading, analyzing and synthesizing information in order to take decisions, and prepare advice and trials, among other tasks. As part of the “Semantic-Based Knowledge and Content Systems” Strategic Objective, the European Commission is funding projects to construct technology to make the Semantic Web vision come true. 1 The articles in this book are related to two current foci of the Strategic Objective : • Knowledge acquisition and modelling, capturing knowledge from raw information and multimedia content in webs and other distributed repositories to turn poorly structured information into machi- processable knowledge.
Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part I
The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.
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 ; 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 Management for Health Care Procedures ; From Knowledge to Global Care, AIME 2007 Workshop K4CARE 2007, Amsterdam, The Netherlands, July 7, 2007, Revised Selected Papers
The incursion of information and communication technologies (ICT) in health care entails evident bene?ts at the levels of security and efciency that improve not only the quality of life of the patients, but also the quality of the work of the health care professionals and the costs of national health care systems. Leaving research approaches aside, the analysis of ICT in health care shows an evo- tion from the initial interest in representing and storing health care data (i. e. , electronic health care records) to the current interest of having remote access to electronic health care systems, as for example HL7 initiatives or telemedicine. This sometimes imperceptible evolution can be interpreted as a new step of the progress path of health care informatics.
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 discovery, knowledge engineering and knowledge management ; 10th International Joint Conference, IC3K 2018, Seville, Spain, September 18-20, 2018, Revised Selected Papers
Constitutes the thoroughly refereed proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2018, held in Seville, Spain, in September 2018. The 12 full papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on knowledge discovery and information retrieval; knowledge engineering and ontology development; and knowledge management and information sharing.
Knowledge Discovery in Databases : PKDD 2007 ; 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings
The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) was?rstheldin1997inTrondheim, Norway.
Knowledge Discovery from XML Documents ; 1st International Workshop, KDXD 2006, Singapore, April 9, 2006, Proceedings
The KDXD 2006 (Knowledge Discovery from XML Documents) workshop is the ?rst international workshop running this year in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2006. The workshop provided an important forum for the dissemination and exchange of new ideas and research related to XML data discovery and retrieval. The eXtensible Markup Language (XML) has become a standard language for data representation and exchange. With the continuous growth in XML data sources,the ability to manage collections of XML documents and discover knowledge from them for decision support becomes increasingly important. Due to the inherent ?exibility ofXML, in both structure and semantics, inferring important knowledge from XML data is faced with new challenges as well as bene?ts. The objective of the workshop was to bring together researchers and practitioners to discuss all aspects of the emerging XML data management challenges.
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.
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.
