الصفحة 21
الصفحة 21
Databases, Information Systems, and Peer-to-Peer Computing ; International Workshops, DBISP2P 2005/2006, Trondheim, Norway, August 28-29, 2006, Revised Selected Papers
The P2P paradigm lends itself to constructing large-scale, complex, adaptive, autonomous and heterogeneous database and information systems, endowed with clearly specified and difierential capabilities to negotiate, bargain, coordinate and self-organize the information exchanges in large-scale networks. This vision will have a radical impact on the structure of complex organizations (business, sci- tific or otherwise) and on the emergence and the formation of social communities, and on how the information is organized and processed. The P2P information paradigm naturally encompasses static and wireless connectivity and static and mobile architectures. Wireless connectivity combined with the increasingly small and powerful mobile devices and sensors poses new challenges as well as opp- tunities to the database community. Information becomes ubiquitous, highly distributed and accessible anywhere and at any time over highly dynamic, - stable networks with very severe constraints on the information management and processing capabilities.
Databases, information systems, and peer-to-peer computing ; 2nd international workshop, DBISP2P 2004, Toronto, Canada, August 29-30, 2004, revised selected papers
Peer-to-peer (P2P) paradigm lends itself to constructing large-scale complex, adaptive, - tonomous and heterogeneous database and information systems, endowed with clearly speci?ed and di?erential capabilities to negotiate, bargain, coordinate, and self-organize the information exchanges in large-scale networks. This vision will have a radical impact on the structure of complex organizations (business, scienti?c, or otherwise) and on the emergence and the formation of social c- munities, and on how the information is organized and processed. The P2P information paradigm naturally encompasses static and wireless connectivity, and static and mobile architectures. Wireless connectivity c- bined with the increasingly small and powerful mobile devices and sensors pose new challenges to as well as opportunities for the database community. Inf- mation becomes ubiquitous, highly distributed and accessible anywhere and at any time over highly dynamic, unstable networks with very severe constraints on the information management and processing capabilities.
Databases in networked information systems; 4th international workshop, DNIS 2005, Aizu-Wakamatsu, Japan, March 28-30, 2005, Proceedings
This book constitutes the refereed proceedings of the 4th International Workshop on Databases in Networked Information Systems, DNIS 2005, held in Aizu-Wakamatsu, Japan in March 2005. The 17 revised full papers presented together with 8 invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on information interchange and management systems, Web data management systems, networked information systems applications, and networked information systems implementations.
Databases in Networked Information Systems ; 5th International Workshop, DNIS 2007, Aizu-Wakamatsu, Japan, October 17-19, 2007, Proceedings
This book Is focusing on data semantics and infrastructure for information management and interchange, the papers are organized in topical sections on geospatial decision-making, Web data management systems, infrastructure of networked information systems, and Web query and web mining systems.
Database Theory – ICDT 2007 ; 11th International Conference, Barcelona, Spain, January 10-12, 2007, Proceedings
The papers are organized in topical sections on information integration and peer to peer, axiomatizations for XML, expressive power of query languages, incompleteness, inconsistency, and uncertainty, XML schemas and typechecking, stream processing and sequential query processing, ranking, XML update and query, as well as query containment.
Database Programming Languages ; 8th International Workshop, DBPL 2001, Frascati, Italy, September 8-10, 2001. Revised Papers
The papers here are organized in topical sections on semistructured data OL AP and data mining systems, schema integration, and index concurrency XML spatial databases user languages and rules.
Database Programming Languages ; 10th international symposium, DBPL 2005, Trondheim, Norway, August 28-29, 2005, revised selected papers
Constitutes the refereed post-proceedings of the 10th International Workshop on Database Programming Languages, DBPL 2005. This book presents papers organized in topical sections on XML languages, XML and P2P data integration, XML query languages, types and XML, grammars, automata, and tree, as well as dependencies and constraints.
Database performance at scale: a practical guide
Optimizing database performance at the scale required for today’s data-intensive applications often requires more than performance tuning and scaling out. This book shares commonly overlooked considerations, pitfalls, and opportunities that have helped many teams break through database performance plateaus. It’s neither a definitive guide to distributed databases nor a beginner’s resource. Rather, it’s a look at the many different factors that impact performance, and our top field-tested recommendations for navigating them. Chapter 1 provides two (fun and fanciful) tales that surface some of the many roadblocks you might face and highlight the range of strategies for navigating around them.
Database and XML Technologies ; Vol. 3671 ; 3rd international XML database symposium, XSym 2005, Trondheim, Norway, August 28-29, 2005, Proceedings
Constitutes the proceedings of the Third International XML Database Symposium, XSym 2005, held in Trondheim, Norway in August 2005. The 15 papers are organized in sections on indexing support for the evaluation of XPath and XQuery; benchmarks and algorithms for XQuery and XPath evaluation; algorithms for constraint satisfaction checking, and more.
Database : Enterprise, skills and innovation; 22nd British national conference on databases, BNCOD 22, Sunderland, UK, July 5-7, 2005, Proceedings
The British National Conference on Databases (BNCOD) was established in 1980 as a forum for research into the theory and practice of databases. The original conference in the series took place at the University of Aberdeen. To be precise, this conference was in fact entitled ICOD which stood for International Conference on Databases. It was the intention, when the series began, that an ICOD would take place every two years, whilst a BNCOD would run in the years in between. As the record shows ICOD was only held in 1980 and 1983. The more junior conference has managed to acquire a lifetime much longer than that of its senior relative! If truth wereknown,however,BNCOD has,overthe years,growninto ICOD and although the conference is still titled “British National,” it is, in fact, an international conference that takes place on a yearly basis. Proof of this can be obtained simply by looking at the table of contents of these proceeding which clearlyshowthatthe majorityofpaperspresentedatthis year’sconferencecame from contributors whose a?liations are outside the UK. Despitetherangeofpapersono?er,BNCODstillretainsitsuniquelyBritish ?avor. The Programme Committee is drawn from UK academics and the c- ference is always held at a British university (or in earlier years a polytechnic!).
Data Warehousing and Knowledge Discovery ; 9th International Conference, DaWaK 2007, Regensburg, Germany, September 3-7, 2007, Proceedings
Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area.
Data Warehousing and Data Mining Techniques for Cyber Security
It provide techniques for collecting information from distributed databases and for performing data analysis. The ever expanding, tremendous amount of data collected and stored in large databases has far exceeded our human ability to comprehend--without the proper tools. There is a critical need for data analysis that can automatically analyze data, summarize it and predict future trends. In the modern age of Internet connectivity, concerns about denial of service attacks, computer viruses and worms are extremely important. Data Warehousing and Data Mining Techniques for Cyber Security contributes to the discipline of security informatics. The author discusses topics that intersect cyber security and data mining, while providing techniques for improving cyber security. Since the cost of information processing and internet accessibility is dropping, an increasing number of organizations are becoming vulnerable to cyber attacks. This volume introduces techniques for applications in the area of retail, finance, and bioinformatics, to name a few.
Data Streams : Models and Algorithms
It primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from that particular topic, and future research directions.
Data security : Technical and organizational protection measures against data loss and computer Crime
Offers an easy-to understand introduction to technical and organizational data security. It provides an insight into the technical knowledge that is mandatory for data protection officers. Data security is an inseparable part of data protection, which is becoming more and more important in our society. It can only be implemented effectively if there is an understanding of technical interrelationships and threats.
Data science, AI, and machine learning in drug development
The confluence of big data, AI, and machine learning has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations
Data science and analytics ; 5th International conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part II
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics
Data science and analytics ; 5th International conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part I
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.
Data science ; 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part II
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
Data Science ; 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part I
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
Data Quality : Concepts, Methodologies and Techniques
Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art.
