This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation. With rapid development of information technology, huge volumes of graph data are accumulated. An availability of rich graph data not only brings great opportunities for realizing big values of data to serve key applications, but also brings great challenges in computation. Using a consistent terminology, the book gives an excellent introduction to the models and algorithms for the problem of cohesive subgraph computation. The materials of this book are well organized from introductory content to more advanced topics while also providing well-designed source codes for most algorithms described in the book. This is a timely book for researchers who are interested in this topic and efficient data structure design for large sparse graph processing. It is also a guideline book for new researchers to get to know the area of cohesive subgraph computation.

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

This book constitutes the refereed proceedings of the 30th Australasian Database Conference, ADC 2019, held in Sydney, NSW, Australia, in January/February 2019. The 9 full papers presented together with one demo paper were carefully reviewed and selected from 19 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research progresses and novel applications of database systems, data management, data mining and data analytics for researchers and practitioners in these areas from Australia, New Zealand and in the world

This two volume set LNCS 10177 and 10178 constitutes the refereed proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 73 full papers, 9 industry papers, 4 demo papers and 3 tutorials were carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization; text mining; recommendation; security, privacy, senor and cloud; social network analytics; map matching and spatial keywords; query processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing; spatial databases; real time data processing; big data; social networks and graphs.

This two volume set LNCS 10177 and 10178 constitutes the refereed proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 73 full papers, 9 industry papers, 4 demo papers and 3 tutorials were carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization; text mining; recommendation; security, privacy, senor and cloud; social network analytics; map matching and spatial keywords; query processing and optimization; search and information retrieval; string and sequence processing; stream date processing; graph and network data processing; spatial databases; real time data processing; big data; social networks and graphs.

This book constitutes the workshop proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 32 full papers and 5 short papers presented were carefully selected and reviewed from 43 submissions to the four following workshops: the 4th International Workshop on Big Data Management and Service, BDMS 2017; the Second International Workshop on Big Data Quality Management, BDQM 2017; the 4th International Workshop on Semantic Computing and Personalization, SeCoP 2017; and the First International Workshop on Data Management and Mining on MOOCs, DMMOOC 2017.

This book constitutes the refereed proceedings of the 27th Australasian Database Conference, ADC 2016, held in Sydney, NSW, Australia, in September 2016. The 33 full papers presented together with 11 demo papers were carefully reviewed and selected from 55 submissions. The mission of ADC is to share novel research solutions to problems of today's information society that fulfill the needs of heterogeneous applications and environments and to identify new issues and directions for future research. The topics of the presented papers are related to all practical and theoretical aspects of advanced database theory and applications, as well as case studies and implementation experiences.

This book constitutes the refereed proceedings of three workshops held at the 18th Asia-Pacific Web Conference, APWeb 2016, in Suzhou, China, in September 2016: the Second International Workshop on Web Data Mining and Applications, WDMA 2016, the First International Workshop on Graph Analytics and Query Processing, GAP 2016, and the First International Workshop on Spatial-temporal Data Management and Analytics, SDMA 2016. The 27 full papers included in this book were carefully reviewed and selected from 37 submissions. The goal of these workshops is to promote the new research directions and applications, especially on web data, graph data, and spatial-temporal data management and analytics.