This book constitutes the refereed proceedings of the 15th Asia-Pacific Conference APWeb 2013 held in Sydney, Australia, in April 2013. The 80 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on distributed processing; graphs; Web search and Web mining; XML, RDF data and query processing; social networks; probabilistic queries; multimedia and visualization; spatial-temporal databases; data mining and knowledge discovery; privacy and security; performance, query processing and optimization. There are also sections summarizing the tutorials and containing the papers from the following workshops: second international workshop on data management for emerging network infrastructure, international workshop on soical media analytics and recommendation technologies, and international workshop on management of spatial temporal data.

This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs. The authors first classify the existing works of CSS over HINs according to the classic cohesiveness metrics such as core, truss, clique, connectivity, density, etc., and then extensively review the specific models and their corresponding search solutions in each group. Note that since the bipartite network is a special case of HINs, all the models developed for general HINs can be directly applied to bipartite networks, but the models customized for bipartite networks may not be easily extended for other general HINs due to their restricted settings. The authors also analyze and compare these cohesive subgraph models (CSMs) and solutions systematically. Specifically, the authors compare different groups of CSMs and analyze both their similarities and differences, from multiple perspectives such as cohesiveness constraints, shared properties, and computational efficiency. Then, for the CSMs in each group, the authors further analyze and compare their model properties and high-level algorithm ideas. This SpringerBrief targets researchers, professors, engineers and graduate students, who are working in the areas of graph data management and graph mining. Undergraduate students who are majoring in computer science, databases, data and knowledge engineering, and data science will also want to read this SpringerBrief.

This two-volume set constitutes the proceedings of the 22nd International Conference on Web Information Systems Engineering, WISE 2021, held in Melbourne, VIC, Australia, in October 2021. The 55 full, 29 short and 5 demo papers, plus 2 tutorials were carefully reviewed and selected from 229 submissions. The papers are organized in the following topical sections: Part I: BlockChain and Crowdsourcing; Database System and Workflow; Data Mining and Applications; Knowledge Graph and Entity Linking; Graph Neural Network; Graph Query; Social Network; Spatial and Temporal Data Analysis. Part II: Deep Learning (1), Deep Learning (2), Recommender Systems (1), Recommender Systems (2), Text Mining (1), Text Mining (2), Service Computing and Cloud Computing (1), Service Computing and Cloud Computing (2), Tutorial and Demo.

This two-volume set constitutes the proceedings of the 22nd International Conference on Web Information Systems Engineering, WISE 2021, held in Melbourne, VIC, Australia, in October 2021. The 55 full, 29 short and 5 demo papers, plus 2 tutorials were carefully reviewed and selected from 229 submissions. The papers are organized in the following topical sections: Part I: BlockChain and Crowdsourcing; Database System and Workflow; Data Mining and Applications; Knowledge Graph and Entity Linking; Graph Neural Network; Graph Query; Social Network; Spatial and Temporal Data Analysis. Part II: Deep Learning (1), Deep Learning (2), Recommender Systems (1), Recommender Systems (2), Text Mining (1), Text Mining (2), Service Computing and Cloud Computing (1), Service Computing and Cloud Computing (2), Tutorial and Demo.

This book constitutes refereed proceedings of the 4th International Workshop on Software Foundations for Data Interoperability, SFDI 2020, and 2nd International Workshop on Large Scale Graph Data Analytics, LSGDA 2020, held in Conjunction with VLDB 2020, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 full papers and 4 short papers were thoroughly reviewed and selected from 38 submissions. The volme presents original research and application papers on the development of novel graph analytics models, scalable graph analytics techniques and systems, data integration, and data exchange.

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.