DBKDA 2024 - The Sixteenth International Conference on Advances in Databases, Knowledge, and Data Applications
March 10, 2024 - March 14, 2024
DBKDA 2024
Onsite and Online Options: In order to accommodate a large number of situations, we are offering the option for either physical presence or virtual participation (pdf slides or pre-recorded videos).
ISSN: 2308-4332
ISBN: 978-1-68558-138-1
DBKDA 2024 is colocated with the following events as part of InfoSys 2024 Congress:
- ICNS 2024, The Twentieth International Conference on Networking and Services
- ICAS 2024, The Twentieth International Conference on Autonomic and Autonomous Systems
- ENERGY 2024, The Fourteenth International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies
- WEB 2024, The Twelfth International Conference on Building and Exploring Web Based Environments
- DBKDA 2024, The Sixteenth International Conference on Advances in Databases, Knowledge, and Data Applications
- SIGNAL 2024, The Ninth International Conference on Advances in Signal, Image and Video Processing
- BIOTECHNO 2024, The Sixteenth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies
- AIHealth 2024, The First International Conference on AI-Health
DBKDA 2024 Steering Committee
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Friedrich Laux
Reutlingen University
Germany
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Lisa Ehrlinger
Software Competence Center Hagenberg GmbH
Austria
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Andreas Schmidt
Karlsruhe Institute of Technology / University of Applied Sciences
Germany
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Peter Kieseberg
St. Pölten University of Applied Sciences
Austria
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Erik Hoel
Esri
USA
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DBKDA 2024 conference tracks:
Advances in fundamentals on databases
Foundations and architectures;
Design features (data quality, performance, robustness, scalability, security, privacy, parallel and distributed approaches, mobility, etc.);
Data quality, data structures, and data modeling;
Advanced indexing methods;
Advanced ranking algorithms and uncertainty;
Physical organization and performance;
Federated choreographies;
Temporal conformance;
Evolutionary clustering and dynamic hierarchical clustering
Knowledge Discovery and Machine Learning
Knowledge extraction via machine learning; Machine learning for datasets; Machine learning and graphs; Graphs analytics and deep learning; Machine learning models (supervised, unsupervised, reinforcement, constrained, etc.); Generative modeling (Gaussian, HMM, GAN, Bayesian networks, autoencoders, etc.); Bayesian learning models; Prediction uncertainty; Training of models (hyperparameter optimization, regularization, optimizers); Active learning (partially labels datasets, faulty labels, semi-supervised); Applications of machine learning (recommender systems, NLP, computer vision, etc.); Data in machine learning (no data, small data, big data, graph data, time series, sparse data, etc.).
NoSQL Databases
Key-value stores; Document stores; Wide-column stores; Graph databases; Spatial databases; Time-series databases; RDF stores; Hybrid DB management systems
Current ongoing researches
DBaaS Storage; Preference-driven databases; Personalized ranking models; Visual query systems; Reverse rank queries; Searching on process description graphs; Search over relational data streams; Linked data streams; Nearby coalescing; Automatic labelling; Personalized query expansion; Benchmarking replication; Community detection; Risk-adaptive security model; Faceted queries over ontologies; Inclusion dependencies; Periodic-frequent patterns; Dynamic query reordering; Queries for linked data; Footprint reduction; Multi-dimensional indexing; Set similarity join algorithms; Incremental continuous query processing; Linkset views; High-utility itemsets; Reputation estimation; Quality prediction; Approximate query answering; Hidden semantic data models; Temporal extractions; Target-oriented keyword search; Filter-based profile matching; Mutual information on data streams; Stream processing; Digitized documents streams; Queries with binary constraints; Propagation granularity; Processing over raw data; Lossy transformations; Queries on massive time series; Generalized indexing; Answering batch queries; Database task schedulers; Similarity search; Fuzzy object databases; Automated prediction of relationships; Linked data streams and Internet of things; Preferred repairs; Parallel-correctness and transferability; Guarded existential rules; Tree pattern containment; Large datasets; Accessing small data; Skyline queries; Distributed set-joins; Stream sampling; Dynamic graph streams; Dynamic data structures; Nearest neighbor search; Data lakes, Knowledge lakes
Databases and other domains
Leading-edge database technology and applications;
Heterogeneous databases interoperability and mediation;
Databases and Web services;
Databases and artificial intelligence;
Databases and agents;
Advances in database management systems;
Advanced transaction and workflow management;
Advances on XML and databases
Databases technologies
Self-managing databases; Mobile databases; Database access; Embedded databases;
Very large scale databases;
Spatial and spatio-temporal databases;
Data warehousing;
Multimedia databases;
Semantic databases;
Data integration resources on the Internet;
Object-oriented databases;
Web-based databases;
Deductive and active databases
Databases content processing
Contextual aggregated information retrieval; Aggregated query for workflows; Mining for complex data;
Mining for text, video, and pictures;
Knowledge discovery and classification;
Process mining;
Scalable data extraction;
Query processing and optimization;
Query rewrite rules;
Navigational path expressions;
Load-balancing in accessing distributed databases;
Incompleteness, inconsistency, uncertainty;
Storage and replication;
Patterns and similarities in data streams;
Fast matching;
Multiple views
Knowledge and decision bases
Knowledge representation and management; Knowledge discovery (business intelligence); Semantic information;
Ontology and advanced knowledge search;
Heuristics and meta-heuristics;
Intelligent knowledge querying;
Feature sampling and feature selection;
Context-aware knowledge base;
Blogs and social relationship search;
Deductive reasoning;
Reasoning databases;
Ontology-based reasoning; Knowledge graphs
Specifics on application domains databases
Database applications in Life Sciences; Advanced database applications;
Bioinformatics databases;
Healthcare databases;
Finance and marketing databases;
Telecom databases;
Geospatial databases;
Census databases;
Meteorological databases;
Business intelligence databases;
e-Business databases
XML-driven data, knowledge, databases
Data /dissemination, distributed, processing, management/; XML-data /storage, exchange, compress, metadata/; XML-data and metadata management; XML repositories; Knowledge discovery from XML repositories; XML-data processing /queries, indexing, management, retrieval, mining/; XML data and knowledge /representation, discovery, mining, orchestration/; XML-data in advances environments /clouds, P2P, multimedia, mobile, finance, biotechnologies, geospatial, space/; XML-data and process /data warehouse, workflow, web, learning, control/;
Data privacy
Privacy models; Privacy metrics; Privacy preservation; Watermarking; Data Hiding; Background knowledge; Privacy /data streams, social networks, databases, semantic web/; Privacy mechanisms /cryptography, privacy-aware access control, generalization-based algoritm, perturbation-based algorithm, preservation, sequental releases/; Practical studies /privacy leaking, privacy breach, threats to privacy, privacy in outsourcing/
Data quality and uncertainty
Models, frameworks, methodologies and metrics for data quality; Quality of complex data /documents, semi-structured data, XMLs, multimedia data, graphs, bio-sequences/; Uncertain and noisy data; Uncertain data representation; Processing uncertain data /querying, indexing, mining/; Mining uncertain data/probabilistic, spatially- and temporally- uncertain, uncertain streams/ Data lineage and provenance; Data profiling and measurement; Data integration, linkage and fusion; D uplicate detection and consistency checking; D ata mining and data quality assessment; Quality methods and algorithms / data transformation, reconciliation, consolidation, extraction, cleansing/; User perception on data quality and cleansing;
Data query, access, mining, and correlation
Data access technologies, Query optimisation, Discovering multi-modal correlations; Mining structural data from non-structural mixed-media documents; Data stream mining /frequent patterns, bursty event detection/; Profile mining; Corelation and anomaly in multi-modal-data /social networks, web traffic logs, sale transactions/; Information retrieval on a mixed collections; Multimedia data mining; Data mining system for medical multimedia data; Contents-based image/video retrieval systems
Data and process provenance
Provenance architectures and algorithms; Provenance modelling; Information management for provenance data; Provenance ontology and semantic; Provenance querying; Provenance annotation; Security, trust, and privacy for provenance information; Case studies and practice; Reasoning over provenance; Provenance analytics, mining and visualization
Data management
Distributed Query Languages; Query processing and optimization; Adaptive query processing; Management of mobile data; Managing data privacy and security; Data storage and management; Data stream systems; Data locating; Data warehouse management; Management of dynamic data; Workload adaptability; Transaction management; Performance evaluation and benchmarking or data management
Deadlines:
Submission | Dec 17, 2023 |
Notification | Jan 20, 2024 |
Registration | Feb 04, 2024 |
Camera ready | Feb 10, 2024 |
Deadlines differ for special tracks. Please consult the conference home page for special tracks Call for Papers (if any).