日本データベース学会の皆様 # 重複して受信された際はご容赦下さい。 いつもお世話になっております。 東海大学情報通信学部の藤野です。 DBKDA 2022（The Fourteenth International Conference on Advances in Databases, Knowledge, and Data Applications)のCFPをお送りいたします。 開催地：イタリア，ベネチア（ベニス） 開催日：5月22-26日 投稿締切日：2月10日 皆様の御投稿をお待ちしております。 どうぞ宜しくお願い致します。 ------------------------------------------------------------- Iwao Fujino Prof., Dr.Eng., Tokai University, Japan Email: fujino@tokai.ac.jp<mailto:fujino@tokai.ac.jp> ------------------------------------------------------------- ________________________________ 差出人: Petre Dini <petre@iaria.org> 送信日時: 2022年1月11日 0:51 宛先: 藤野　巖 <fujino@tokai.ac.jp> 件名: 3rd CfP: DBKDA 2022 || May 22 - 26, 2022 - Venice, Italy INVITATION: ================= Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to: - DBKDA 2022, The Fourteenth International Conference on Advances in Databases, Knowledge, and Data Applications DBKDA 2022 is scheduled to be May 22 - 26, 2022 in Venice, Italy under the InfoSys 2022 umbrella. The submission deadline is scheduled for February 10, 2022. Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: https://www.iariajournals.org All events will be held in a hybrid mode: on site, online, prerecorded videos, voiced presentation slides, pdf slides. ================= ============== DBKDA 2022 | Call for Papers =============== CALL FOR PAPERS, TUTORIALS, PANELS DBKDA 2022, The Fourteenth International Conference on Advances in Databases, Knowledge, and Data Applications General page: https://www.iaria.org/conferences2022/DBKDA22.html Submission page: https://www.iaria.org/conferences2022/SubmitDBKDA22.html Event schedule: May 22 - 26, 2022 Contributions: - regular papers [in the proceedings, digital library] - short papers (work in progress) [in the proceedings, digital library] - ideas: two pages [in the proceedings, digital library] - extended abstracts: two pages [in the proceedings, digital library] - posters: two pages [in the proceedings, digital library] - posters: slide only [slide-deck posted at www.iaria.org]<http://www.iaria.org]> - presentations: slide only [slide-deck posted at www.iaria.org]<http://www.iaria.org]> - demos: two pages [posted at www.iaria.org]<http://www.iaria.org]> Submission deadline: February 10, 2022 Extended versions of selected papers will be published in IARIA Journals: https://www.iariajournals.org Print proceedings will be available via Curran Associates, Inc.: https://www.proceedings.com/9769.html Articles will be archived in the free access ThinkMind Digital Library: https://www.thinkmind.org The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas. All tracks are open to both research and industry contributions. Before submission, please check and comply with the editorial rules: https://www.iaria.org/editorialrules.html DBKDA 2022 Topics (for topics and submission details: see CfP on the site) Call for Papers: https://www.iaria.org/conferences2022/CfPDBKDA22.html ============================================================ DBKDA 2022 Tracks (topics and submission details: see CfP on the site) 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 ------------------------ DBKDA 2022 Committee: https://www.iaria.org/conferences2022/ComDBKDA22.html