TheInternationalConferenceonScienti?candStatisticalDatabaseManagement (SSDBM)isanestablishedforumfortheexchangeofthelatestresearchresultson concepts, tools, andtechniquesforscienti?candstatisticaldatabaseapplications. The2008meetingmarkedthe20thtimethatscienti?cdomainexperts, databases researchers, practitioners, and developers came together to share their new - sightsand to discuss ina stimulating environmentfuture researchdirections. This volume contains the proceedings of the 20th SSDBM Conference, held in Hong Kong, China, July 9-11,2008.The conference included 3 keynote talks, 28 long and 7 short papers in 9 sessions, and 8 posters and demonstrations in a single session. Distinguishedmembersofthe communitydeliveredthethree keynotes, which wereabout the past, present, and future managementof scienti?c and statistical data. Alex Szalay, an expert in large-scalescienti?c data management, discussed "New Challenges in Petascale Scienti?c Databases," managing huge scienti?c data repositories, with a focus on particular examples taken from astronomy. Nick Koudas, a leader in semi-structured text management, talked about "- ventures in the Blogosphere," a huge network of textual data (including blogs, social networks, wikis), and BlogScope, a system that collects and analyzes such data. Finally, Per Svensson, a pioneer in database systems development for s- enti?c applications, provided a historical review on "The Evolution of Vertical Database Architectures" from the perspective and performance needs of a s- enti?c or statistical large-scale data analyst user. The Program Committee, consisting of 37 members, accepted 43 papers (28 long,7short, and8posters/demos)fromatotalof84submissions.Thereviewing process was managed by the EasyChair Conference System, an excellent free conference management system, developed by Andrei Voronkov.

SSTD 2009 was the 11th in a series of biannual events that discuss new and exciting research in spatio-temporal data management and related technologies. PrevioussymposiaweresuccessfullyheldinSantaBarbara(1989),Zurich(1991), Singapore (1993), Portland (1995), Berlin (1997), Hong Kong (1999), Los An- les (2001), Santorini, Greece (2003), Angra dos Reis, Brazil (2005), and Boston (2007). Before 2001, the series was devoted solely to spatial database mana- ment, and called SSD. From 2001, the scope was extended in order to also accommodate temporal database management, in part due to the increasing importance of research that considers spatial and temporal aspects jointly. SSTD2009introducedseveralinnovativeaspectscomparedtopreviousevents. There was a demonstrations track which included ten presentations of systems related to the topics of interest. In addition to that, the event included a poster session with seven presentations of innovative research developed at an early stage. For the ?rst time in the SSTD series, the best paper of the symposium was awarded and a few high-quality papers were selected and the authors were invited to submit extended versionsof their work to a special issue of the Geo- formatica journal (Springer). Prior to the symposium, there was a two-day - vanced seminar, which hosted three half-day tutorials on state-of-the-art topics within spatio-temporal data management, held by distinguished international researchers.

This book constitutes the proceedings of the 20th International Conference on Web Information Systems Engineering, WISE 2019, held in Hong Kong, China, in November 2019. Due to the problems/protests in Hong Kong, WISE 2019 was postponed from November 26-30, 2019 until January 19-22, 2020. The 50 full papers presented were carefully reviewed and selected from 211 submissions. The papers are organized in the following topical sections: blockchain and crowdsourcing; machine learning; deep learning; recommender systems, data mining; web-based applications; entity linkage and disambiguation; graph learning; knowledge graphs; graph mining; and text mining.

Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Table of Contents: Introduction / Spatial Data / Indexing / Spatial Query Evaluation / Spatial Networks / Applications of Spatial Data Management Technology