Data Science
- 33 %

Data Science

30th British International Conference on Databases, BICOD 2015, Edinburgh, UK, July 6-8, 2015, Proceedings
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Sebastian Maneth
376 g
235x155x13 mm
9147, Lecture Notes in Computer Science Information Systems and Applications, incl. Internet/Web, and HCI

This book constitutes the refereed conference proceedings of the 30th British International Conference on Databases, BICOD 2015 - formerly known as BNCOD (British National Conference on Databases) - held in Edinburgh, UK, in July 2015.
The 19 revised full papers, presented together with three invited
keynotes and three invited lectures were carefully reviewed and selected from 37 submissions. Special focus of the conference has been "Data Science" and so the papers cover a wide range of topics related to databases and data-centric computation.
Streaming Methods in Data Analysis.- A Framework for Scalable Correlation of Spatio-temporal Event Data.- Towards More Data-Aware Application Integration.- Applying NoSQL Databases for Integrating Web Educational Stores - An Ontology-Based Approach.- Implementing Peer-to-Peer Semantic Integration of Linked Data.- Virtual Network Mapping: A Graph Pattern Matching Approach.- A Fast Approach for Detecting Overlapping Communities in Social Networks Based on Game Theory.- Consistent RDF Updates with Correct Dense Deltas.- Query-Oriented Summarization of RDF Graphs.- ReX: Extrapolating Relational Data in a Representative Way.- Evaluation Measures for Event Detection Techniques on Twitter Data Streams.- A Framework for Selecting Deep Learning Hyper-parameters.- Using Virtual Meeting Structure to Support Summarisation.- NotaQL Is Not a Query Language! It's for Data Transformation on Wide-Column Stores.- NoSQL Approach to Large Scale Analysis of Persisted Streams.- Horizontal Fragmentation and Replication for Multiple Relaxation Attributes.- Scalable Queries Over Log Database Collections.- ECST - Extended Context-Free Straight-Line Tree Grammars.- Configuring Spatial Grids for Efficient Main Memory Joins.- Transactional and Incremental Type Inference from Data Updates.