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Database and XMLTechnologies ; 5th International XML Database Symposium, XSym 2007, Vienna, Austria, September 23-24, 2007, Proceedings
This book discuss the use of and synergy between databases and XML. It provided theory and practice of XML data management and its applications. This volume also contains current research in XPath and XQuery processing, XML Updates, Temporal XML and Constraints.
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 and expert systems applications ; DEXA 2020 International workshops BIOKDD, IWCFS and MLKgraphs, Bratislava, Slovakia, September 14–17, 2020, Proceedings
This volume constitutes the refereed proceedings of the three workshops held at the 31st International Conference on Database and Expert Systems Applications, DEXA 2020, held in September 2020: The 11th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2020, the 4th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2020, the 2nd International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019. Due to the COVID-19 pandemic the conference and workshop were held virtually. The 10 papers were thoroughly reviewed and selected from 15 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligent.
Database and Expert Systems Applications ; 18th International Conference, DEXA 2007, Regensburg, Germany, September 3-7, 2007, Proceedings
This volume represent the state of the art of - search in the domain of data, information and knowledge management, intelligent systems, and their applications.
Database and expert systems and Aapplications ; 17th International Conference, DEXA 2006, Krakow, Poland, September 4-8, 2006, Proceedings
The annual international conference on Database and Expert Systems Applications (DEXA) is now well established as a reference scientific event. The reader will find in this volume a collection of scientific papers that represent the state of the art of research in the domain of data, information and knowledge management, intelligent systems, and their applications.
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 ; Vol.4081 ; 8th International Conference, DaWaK 2006, Krakow, Poland, September 4-8, 2006, Proceedings
DaWaK aimed at providing the right and logical balance between data warehousing and knowledge discovery. In data warehousing the papers cover different research problems, such as advanced techniques in OLAP visuali- tion and multidimensional modelling, innovation of ETL processes and integration problems, materialized view optimization, very large data warehouse processing, data warehouses and data mining applications integration, data warehousing for real-life applications, e. g. , medical applications and spatial applications. In data mining and knowledge discovery, papers are focused on a variety of topics from data streams analysis and mining, ontology-based mining techniques, mining frequent item sets, clustering, association and classification, patterns and so on.
Data Warehousing and Knowledge Discovery ; 4th International Conference, DaWaK 2002, Aix-en-Provence, France, September 4-6, 2002. Proceedings
Within the last few years Data Warehousing and Knowledge Discovery technology has established itself as a key technology for enterprises that wish to improve the quality of the results obtained from data analysis, decision support, and the automatic extraction of knowledge from data. The Fourth International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2002) continues a series of successful conferences dedicated to this topic. Its main objective is to bring together researchers and practitioners to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions.
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 on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
Data science for economics and finance : Methodologies and applications
The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
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 ; 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 and Record Linkage Techniques
This book helps practitioners gain a deeper understanding, at an applied level, of the issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models. Here, we focus on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. Brief examples are included to show how these techniques work. In the second part of the book, the authors present real-world case studies in which one or more of these techniques are used. They cover a wide variety of application areas. These include mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists.
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.
Data parallel C++programming accelerated systems using C++ and SYCL
Full of practical advice, detailed explanations, and code examples to illustrate key topics. SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand. This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations.
