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New Trends in Data Warehousing and Data Analysis
Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.
Business Intelligence
To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the “Big Data” phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into acco...
Model and Data Engineering
This book constitutes the refereed proceedings of the 10th International Conference on Model and Data Engineering, MEDI 2021, held in Tallinn, Estonia, in June 2021. The 16 full papers and 8 short papers presented in this book were carefully reviewed and selected from 47 submissions. Additionally, the volume includes 3 abstracts of invited talks. The papers cover broad research areas on both theoretical, systems and practical aspects. Some papers include mining complex databases, concurrent systems, machine learning, swarm optimization, query processing, semantic web, graph databases, formal methods, model-driven engineering, blockchain, cyber physical systems, IoT applications, and smart systems. Due to the Corona pandemic the conference was held virtually.
Data Analytics for Renewable Energy Integration
This book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
Advances in Database Technology -- EDBT 2006
This book constitutes the refereed proceedings of the 10th International Conference on Extending Database Technology, EDBT 2006, held in Munich, Germany, in March 2006. The 60 revised research papers presented together with eight industrial application papers, 20 software demos, and three invited contributions were carefully reviewed and selected from 352 submissions. The papers are organized in topical sections.
Knowledge-Based and Intelligent Information and Engineering Systems
The four-volume set LNAI 6276--6279 constitutes the refereed proceedings of the 14th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2010, held in Cardiff, UK, in September 2010. The 272 revised papers presented were carefully reviewed and selected from 360 submissions. They present the results of high-quality research on a broad range of intelligent systems topics.
Similarity Joins in Relational Database Systems
State-of-the-art database systems manage and process a variety of complex objects, including strings and trees. For such objects equality comparisons are often not meaningful and must be replaced by similarity comparisons. This book describes the concepts and techniques to incorporate similarity into database systems. We start out by discussing the properties of strings and trees, and identify the edit distance as the de facto standard for comparing complex objects. Since the edit distance is computationally expensive, token-based distances have been introduced to speed up edit distance computations. The basic idea is to decompose complex objects into sets of tokens that can be compared effi...
Advances in Information Systems
This volume contains the proceedings of the 3rd International Conference on AdvancesinInformationSystems(ADVIS)heldinIzmir,Turkey,20–22October, 2004. This was the third conference dedicated to the memory of Prof. Esen Ozkarahan. We are very proud to continue this tradition and keep the memory of this outstanding scientist. The third conference covered many of the topics of the second one: databases and data warehouses, information systems development and management, - formation retrieval, distributed and parallel data processing, and evolutionary algorithms. Besides them some of the hot topics related to information systems were included in the scope of this conference, such as data mining...
On the Move to Meaningful Internet Systems 2005: CoopIS, DOA, and ODBASE
This two-volume set LNCS 3760/3761 constitutes the refereed proceedings of the three confederated conferences CoopIS 2005, DOA 2005, and ODBASE 2005 held as OTM 2005 in Agia Napa, Cyprus in October/November 2005. The 89 revised full and 7 short papers presented together with 3 keynote speeches were carefully reviewed and selected from a total of 360 submissions. Corresponding with the three OTM 2005 main conferences CoopIS, DOA, and ODBASE, the papers are organized in topical sections on workflow, workflow and business processes, mining and filtering, petri nets and processs management, information access and integrity, heterogeneity, semantics, querying and content delivery, Web services, a...
Data Warehousing and Knowledge Discovery
Data warehousing and knowledge discovery has been widely accepted as a key te- nology 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 considered become more and more complex in both structure and semantics. New developments such as cloud computing add to the challenges with massive scaling, a new computing infrastructure, and new types of data. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data forms the litmus test...
