Algorithms and data structures

Due to the Internet Revolution, human conversational data -- in written forms -- are accumulating at a phenomenal rate.

Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability.

Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency.

This book is a gentle introduction to dominance-based query processing techniques and their applications.

Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: flexible structure, optional schema, and rich, flexible Universal Resource Identifiers as a basis for information sharing.

Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks.

Nowadays, textual databases are among the most rapidly growing collections of data.

Since the introduction of Bitcoin-the first widespread application driven by blockchain-the interest of the public and private sectors in blockchain has skyrocketed.

This book contains a number of chapters on transactional database concurrency control.

The topic of using views to answer queries has been popular for a few decades now, as it cuts across domains such as query optimization, information integration, data warehousing, website design and, recently, database-as-a-service and data placement in cloud systems.

The last decade has brought groundbreaking developments in transaction processing.

Workflows may be defined as abstractions used to model the coherent flow of activities in the context of an in silico scientific experiment.

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications.

This book explores the implications of non-volatile memory (NVM) for database management systems (DBMSs).

Data usually comes in a plethora of formats and dimensions, rendering the exploration and information extraction processes challenging.

Data profiling refers to the activity of collecting data about data, {i.

Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity.

Incomplete data is part of life and almost all areas of scientific studies.

The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts.

Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data.

Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us.

Text data that is associated with location data has become ubiquitous.

Data management systems enable various influential applications from high-performance online services (e.

Traditional theory and practice of write-ahead logging and of database recovery focus on three failure classes: transaction failures (typically due to deadlocks) resolved by transaction rollback; system failures (typically power or software faults) resolved by restart with log analysis, "e;redo,"e; and "e;undo"e; phases; and media failures (typically hardware faults) resolved by restore operations that combine multiple types of backups and log replay.

Query reformulation refers to a process of translating a source query-a request for information in some high-level logic-based language-into a target plan that abides by certain interface restrictions.

On the Web, a massive amount of user-generated content is available through various channels (e.

The use of logic in databases started in the late 1960s.

The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society.

State-of-the-art database systems manage and process a variety of complex objects, including strings and trees.

Research on social networks has exploded over the last decade.

Roughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing.

This lecture introduces systematically into the problem of managing large data collections in peer-to-peer systems.

In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "e;How did our sales perform during the last quarter?

Ranking queries are widely used in data exploration, data analysis and decision making scenarios.

Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous, distributed data sources.

Among the search tools currently on the Web, search engines are the most well known thanks to the popularity of major search engines such as Google and Yahoo!

One of the application areas of data mining is the World Wide Web (WWW or Web), which serves as a huge, widely distributed, global information service for every kind of information such as news, advertisements, consumer information, financial management, education, government, e-commerce, health services, and many other information services.

Object-oriented databases were originally developed as an alternative to relational database technology for the representation, storage, and access of non-traditional data forms that were increasingly found in advanced applications of database technology.

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses.

Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of the relationship between the source and the target.

This lecture covers several core issues in user-centered data management, including how to design usable interfaces that suitably support database tasks, and relevant approaches to visual querying, information visualization, and visual data mining.

Many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining.

Access control is one of the fundamental services that any Data Management System should provide.

With the ever increasing volume of data, data quality problems abound.

Privacy preservation has become a major issue in many data analysis applications.

Database replication is widely used for fault-tolerance, scalability and performance.

In the new edition of Neural Assemblies, the author places his original ideas and motivations within the framework of modern and cognitive neuroscience and gives a short and focused overview of the development of computational neuroscience and artificial neural networks over the last 40 years.

The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021.

This book constitutes the proceedings of the 20th International Symposium on Intelligent Data Analysis, IDA 2022, which was held in Rennes, France, during April 20-22, 2022.

This volume gives an up-to-date review of the subject Integration in Finite Terms.