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This book examines the recent trend of extending data dependencies to adapt to rich data types in order to address variety and veracity issues in big data. Readers will be guided through the full range of rich data types where data dependencies have been successfully applied, including categorical data with equality relationships, heterogeneous data with similarity relationships, numerical data with order relationships, sequential data with timestamps, and graph data with complicated structures. The text will also discuss interesting constraints on ordering or similarity relationships contained in novel classes of data dependencies in addition to those in equality relationships, e.g., considered in functional dependencies (FDs). In addition to exploring the concepts of these data dependency notations, the book investigates the extension relationships between data dependencies, such as conditional functional dependencies (CFDs) that extend conventional functional dependencies (FDs). This forms in the book a family tree of extensions, mostly rooted in FDs, that help illuminate the expressive power of various data dependencies. Moreover, the book points to work on the discovery of dependencies from data, since data dependencies are often unlikely to be manually specified in a traditional way, given the huge volume and high variety in big data. It further outlines the applications of the extended data dependencies, in particular in data quality practice. Altogether, this book provides a comprehensive guide for readers to select proper data dependencies for their applications that have sufficient expressive power and reasonable discovery cost. Finally, the book concludes with several directions of future studies on emerging data.

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology fordesigning efficient large-scale graph algorithms.

Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.

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 two –volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.

This two –volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.

This book constitutes the refereed proceedings of the 16th Asia-Pacific Conference APWeb 2014 held in Changsha, China, in September 2014. The 34 full papers and 23 short papers presented were carefully reviewed and selected from 134 submissions. The papers address research, development and advanced applications of large-scale data management, web and search technologies, and information processing.

Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book serves as a comprehensive guideline for query processing over uncertain databases. Table of Contents: Introduction / Uncertain Data Models / Spatial Query Semantics over Uncertain Data Models / Spatial Query Processing over Uncertain Databases / Conclusion

This book constitutes the workshop proceedings of the 18th International Conference on Database Systems for Advanced Applications, DASFAA 2013, held in Wuhan, China, in April 2013. The volume contains three workshops, each focusing on specific area that contributes to the main themes of the DASFAA conference: The First International Workshop on Big Data Management and Analytics (BDMA 2013), the Third International Workshop on Social Networks and Social Web (SNSM 2013) and the International Workshop on Semantic Computing and Personalization (SeCoP 2013).

This book constitutes the refereed proceedings of the 13th International Conference on Web-Age Information Management, WAIM 2012, held in Harbin, China in August 2012. The 32 revised full papers presented together with 10 short papers and three keynotes were carefully reviewed and selected from a total of 178 submissions. The papers are organized in topical sections on wireless sensor networks; data warehousing and data mining; query processing; spatial databases; similarity search and queries; XML and Web data; graph and uncertain data; distributed computing; data security and management; information extraction and integration; and social networks and modern Web services.

th Welcome to the Proceedings of WISE 2010 — the 11 International Conference on Web Information Systems Engineering. This year, WISE returned to the place where the inaugural conference was held in 2000, Hong Kong. WISE has also been held in: 2001 Kyoto (Japan), 2002 Singapore, 2003 Rome (Italy), 2004 Brisbane (Australia), 2005 New York (USA), 2006 Wuhan (China), 2007 Nancy (France), 2008 Auckland (New Zealand), and 2009 Poznan (Poland). Continuing its trend, this year's WISE provided a forum for engineers and scientists to present their latest findings in Web-related technologies and solutions. The submitted contributions address challenging issues in Web services, search, modeling, recommendation and data mining, as well as keyword search, social network analysis, query languages, and information retrieval and extraction. This year, WISE received 170 submissions from 25 countries, including Argentina, Australia, Austria, Belgium, Canada, China, Czech Republic, France, Germany, Hong Kong, Greece, Iran, Ireland, Italy, Japan, The Netherlands, Norway, Singapore, South Korea, Spain, Sweden, Switzerland, Taiwan, UK, and the USA. After a thorough reviewing process, 32 papers were selected for presentation as full papers – the acceptance rate was 18.8%. In addition, 19 papers were selected for presentation as short papers, yielding an overall acceptance rate of 30%.

DASFAA is an annual international database conference, located in the Asia- Paci?cregion,whichshowcasesstate-of-the-artR & Dactivities in databases- tems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry. DASFAA 2009, the 14th in the series, was held during April 20-23, 2009 in Brisbane, Australia. In this year, we carefully selected six workshops, each focusing on speci?c research issues that contribute to the main themes of the DASFAA conference. Thisvolumecontainsthe?nalversionsofpapersacceptedforthesesixworkshops that were held in conjunction with DASFAA 2009. They are: – First International Workshop on Benchmarking of XML and Semantic Web Applications (BenchmarX 2009) – Second International Workshop on Managing Data Quality in Collaborative Information Systems (MCIS 2009) – First International Workshop on Data and Process Provenance (WDPP 2009) – First International Workshop on Privacy-Preserving Data Analysis (PPDA 2009) – FirstInternationalWorkshoponMobileBusinessCollaboration(MBC2009) – DASFAA 2009 PhD Workshop All the workshops were selected via a public call-for-proposals process. The workshop organizers put a tremendous amount of e?ort into soliciting and - lecting papers with a balance of high quality, new ideas and new applications. We asked all workshops to follow a rigid paper selection process, including the procedure to ensure that any Program Committee members are excluded from the paper review process of any paper they are involved with. A requirement about the overall paper acceptance rate of no more than 50% was also imposed on all the workshops.