Databases Theory and Applications
26th Australasian Database Conference, ADC 2015, Melbourne, VIC, Australia, June 4-7, 2015. Proceedings
Published on 28. May 2015
Book
Paperback/Softback
XXV, 334 pages
978-3-319-19547-6 (ISBN)
Description
This book constitutes the refereed proceedings of the 26th Australasian Database Conference, ADC 2015, held in Melbourne, VIC, Australia, in June 2015. The 24 full papers presented together with 5 demo papers were carefully reviewed and selected from 43 submissions.
The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data driven applications and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. 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. ADC seeks papers from academia and industry presenting research on all practical and theoretical aspects of advanced database theory and applications, as well as case studies and implementation experiences.
More details
Series
Edition
2015 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
130 s/w Abbildungen
XXV, 334 p. 130 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 20 mm
Weight
546 gr
ISBN-13
978-3-319-19547-6 (9783319195476)
DOI
10.1007/978-3-319-19548-3
Schweitzer Classification
Other editions
Additional editions
Mohamed A. Sharaf | Muhammad Aamir Cheema | Jianzhong Qi
Databases Theory and Applications
26th Australasian Database Conference, ADC 2015, Melbourne, VIC, Australia, June 4-7, 2015. Proceedings
E-Book
05/2015
Springer
€53.49
Available for download
Content
Research papers.- Efficient Discovery of Differential Dependencies through Association Rules Mining.- Ontology Augmentation via Attribute Extraction from Multiple Types of Sources.- Predicting Passengers in Public Transportation Using Smart Card Data.- Unifying Spatial, Temporal and Semantic Features for an Effective GPS Trajectory-Based Location Recommendation.- A Cache-based Semi-Stream Join to deal with Unmatched Stream Data.- Storing and Processing Massive Trajectory Data on SAP HANA.- Belief Revision in Uncertain Data Integration.- Personal Process Description Graph for Describing and Querying Personal Processes.- Predicting the Spread of a New Tweet in Twitter.- Improvement of Join Algorithms for Low-Selectivity Joins on MapReduce.- Predicting Users' Purchasing Behaviors Using Their Browsing History.- Bus Arrival Time using a Modified Amalgamation of Fuzzy Clustering and Neural Network on Spatio-temporal Data.- A Domain Independent Approach for Extracting Terms from Research Papers.- TK-SK: Textual-restricted K Spatial Keyword Query on Road Networks.- Handling Query Skew in Large Indexes: A View Based Approach.- Effective Spatial Keyword Query Processing on Road Networks.- Cognition and Statistical-based Crowd Evaluation Framework for ER-In-house Crowdsourcing System: Inbound Contact Center.- Community Based Information Dissemination.- A Fast and Effective Image Geometric Verification Method for Efficient CBIR.- Efficient Mining of Non-derivable Emerging Patterns.- Using Word Embeddings to Enhance Keyword Identification for Scientific Publications.- Truth discovery in Material Science databases.- Presto-RDF: SPARQL Querying over Big RDF Data.- Detecting Spamming Groups in Social Media Based on Latent Graph.- Demo papers.- A Framework of Enriching Business Processes Life-Cycle with Tagging Information.- SocialTrail: Recommending Social Trajectories from Location-Based Social Networks.- SocialAnalysis: A Real-time Query and Mining System from Social Media DataStreams.- SCIT: A Schema Change Interpretation Tool for Dynamic-Schema Data Warehouses.- SEMI: A Scalable Entity Matching System based on MapReduce.