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Foundations of Data Quality Management
Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the...
Veracity of Data
On the Web, a massive amount of user-generated content is available through various channels (e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc.). Conflicting information, rumors, erroneous and fake content can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. This book gives an overview of fundamental issues and recent contributions for ascertaining the veracity of data in the era of Big Data. The text is organized into six chapters, focusing on structured data extracted from texts. Chapter 1 introduces the problem of ascertaining the veracity of data in a multi-source and evolving context. Issues relate...
Resource Discovery
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Resource Discovery, RED 2010, held in Paris, France, in November 2010. The 13 revised full papers - from 24 initial submissions - were carefully selected during a second round of reviewing and improvement from the lectures given at the workshop and are presented in extended version in the book. They deal with the following topics: resource discovery for composition; bioinformatics resource discovery; textual resource discovery; and Web service discovery.
Quality Measures in Data Mining
This book presents recent advances in quality measures in data mining.
Database Systems for Advanced Applications
This book constitutes the workshop proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018. The 23 full papers presented were carefully selected and reviewed from 44 submissions to the four following workshops: the 5th International Workshop on Big Data Management and Service, BDMS 2018; the Third International Workshop on Big Data Quality Management, BDQM 2018; the Second International Workshop on Graph Data Management and Analysis, GDMA 2018; and the 5th International Workshop on Semantic Computing and Personalization, SeCoP 2018.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops:Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021)Workshop on Parallel, Distributed and Federated Learning (PDFL 2021)Workshop on Graph Embedding and Mining (GEM 2021)Workshop on Machine L...
Conceptual Modeling - ER 2001
This book constitutes the refereed proceedings of the 20th International Conference on Conceptual Modeling, ER 2001, held in Tokohama, Japan, in November 2001. The 45 revised full papers presented together with three keynote presentations were carefully reviewed and selected from a total of 197 submissions. The papers are organized in topical sections on spatial databases, spatio-temporal databases, XML, information modeling, database design, data integration, data warehouse, UML, conceptual models, systems design, method reengineering and video databases, workflows, web information systems, applications, and software engineering.
Handbook of Data Quality
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged....
Principles of Data Integration
How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications.
New Trends in Databases and Information Systems
This book constitutes the thoroughly refereed short papers, workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019, held in Bled, Slovenia, in September 2019. The 19 short research papers and the 5 doctoral consortium papers were carefully reviewed and selected from 103 submissions, and the 31 workshop papers were selected out of 67 submitted papers. The papers are organized in the following sections: Short Papers; Workshops Papers; Doctoral Consortium Papers; and cover a wide spectrum of topics related to database and information systems technologies for advanced applications.
