Managing And Mining Graph Data

Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 1441960457
Size: 18.19 MB
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Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.

Advancing Big Data Benchmarks

Author: Tilmann Rabl
Publisher: Springer
ISBN: 3319105965
Size: 38.39 MB
Format: PDF, Kindle
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This book constitutes the thoroughly refereed joint proceedings of the Third and Fourth Workshop on Big Data Benchmarking. The third WBDB was held in Xi'an, China, in July 2013 and the Fourth WBDB was held in San José, CA, USA, in October, 2013. The 15 papers presented in this book were carefully reviewed and selected from 33 presentations. They focus on big data benchmarks; applications and scenarios; tools, systems and surveys.

Principle Advancements In Database Management Technologies New Applications And Frameworks

Author: Siau, Keng
Publisher: IGI Global
ISBN: 1605669059
Size: 70.19 MB
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Significant progression and usage of Internet innovations has caused a need for streamlining past, present, and future database technologies. Principle Advancements in Database Management Technologies: New Applications and Frameworks presents exemplary research in a variety of areas related to database development, technology, and use. This authoritative reference source presents innovative approaches by leading international experts to serve as the primary database management source for researchers, practitioners, and academicians.

Database Systems For Advanced Applications

Author: Jian Pei
Publisher: Springer
ISBN: 3319914529
Size: 17.45 MB
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This two-volume set LNCS 10827 and LNCS 10828 constitutes the refereed proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018. The 83 full papers, 21 short papers, 6 industry papers, and 8 demo papers were carefully selected from a total of 360 submissions. The papers are organized around the following topics: network embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming data; RDF and knowledge graphs; text and data mining; medical data mining; security and privacy; search and information retrieval; query processing and optimizations; data quality and crowdsourcing; learning models; multimedia data processing; and distributed computing.

Advances In Databases And Information Systems

Author: Tadeusz Morzy
Publisher: Springer Science & Business Media
ISBN: 3642327419
Size: 62.57 MB
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This volume is the second one of the 16th East-European Conference on Advances in Databases and Information Systems (ADBIS 2012), held on September 18-21, 2012, in Poznań, Poland. The first one has been published in the LNCS series. This volume includes 27 research contributions, selected out of 90. The contributions cover a wide spectrum of topics in the database and information systems field, including: database foundation and theory, data modeling and database design, business process modeling, query optimization in relational and object databases, materialized view selection algorithms, index data structures, distributed systems, system and data integration, semi-structured data and databases, semantic data management, information retrieval, data mining techniques, data stream processing, trust and reputation in the Internet, and social networks. Thus, the content of this volume covers the research areas from fundamentals of databases, through still hot topic research problems (e.g., data mining, XML data processing), to novel research areas (e.g., social networks, trust and reputation, and data stream processing). The editors of this volume believe that its content will inspire the researchers with new ideas for future development. It may also serve as an overview of the ongoing work in the field of databases and information systems.

Advanced Data Management

Author: Lena Wiese
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110441411
Size: 65.44 MB
Format: PDF, Mobi
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This book provides a formal analysis of alternative, non-relational data models and storage mechanisms and gives a decent overview of non-SQL query languages. It describes a perspective beyond SQL and relational database management systems and thus covers the theoretical background of modern data management. It also helps to take informed decisions about what database systems to use.

Keyword Search In Databases

Author: Jeffrey Xu Yu
Publisher: Morgan & Claypool Publishers
ISBN: 160845195X
Size: 27.16 MB
Format: PDF, Mobi
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It has become highly desirable to provide users with flexible ways to query/search information over databases as simple as keyword search like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information among objects in a database using a set of keywords. Such structural information to be returned can be either trees or subgraphs representing how the objects, that contain the required keywords, are interconnected in a relational database or in an XML database. The structural keyword search is completely different from finding documents that contain all the user-given keywords. The former focuses on the interconnected object structures, whereas the latter focuses on the object content. The book is organized as follows. In Chapter 1, we highlight the main research issues on the structural keyword search in different contexts. In Chapter 2, we focus on supporting structural keyword search in a relational database management system using the SQL query language. We concentrate on how to generate a set of SQL queries that can find all the structural information among records in a relational database completely, and how to evaluate the generated set of SQL queries efficiently. In Chapter 3, we discuss graph algorithms for structural keyword search by treating an entire relational database as a large data graph. In Chapter 4, we discuss structural keyword search in a large tree-structured XML database. In Chapter 5, we highlight several interesting research issues regarding keyword search on databases. The book can be used as either an extended survey for people who are interested in the structural keyword search or a reference book for a postgraduate course on the related topics. Table of Contents: Introduction / Schema-Based Keyword Search on Relational Databases / Graph-Based Keyword Search / Keyword Search in XML Databases / Other Topics for Keyword Search on Databases

Mining Of Massive Datasets

Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Size: 75.22 MB
Format: PDF, Mobi
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Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Managing And Mining Uncertain Data

Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 0387096906
Size: 22.99 MB
Format: PDF
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Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.

Data Mining Concepts And Techniques

Author: Jiawei Han
Publisher: Elsevier
ISBN: 9780123814807
Size: 44.85 MB
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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data