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190924 ||| eng |
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|a 9783030276157
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|a Hartmann, Sven
|e [editor]
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|a Database and Expert Systems Applications
|h Elektronische Ressource
|b 30th International Conference, DEXA 2019, Linz, Austria, August 26–29, 2019, Proceedings, Part I
|c edited by Sven Hartmann, Josef Küng, Sharma Chakravarthy, Gabriele Anderst-Kotsis, A Min Tjoa, Ismail Khalil
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|a 1st ed. 2019
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|a Cham
|b Springer International Publishing
|c 2019, 2019
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|a XXVI, 447 p. 233 illus., 111 illus. in color
|b online resource
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|a Discovering Diverse Popular Paths using Transactional Modeling and Patter Mining -- Data Mining and Warehousing -- Representative Sample Extraction from Web Data Streams -- LogLInc: LoG Queries of Linked open data Investigator for Cube Design -- Handling the Information Backlog for Data Warehouse Development -- Ontario: Federated Query Processing against a Semantic Data Lake -- A Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition -- Named Entity Recognition in Local Intent Web Search Queries -- Database Processing-in-Memory: A Vision -- Context-Aware GANs for Image Generation from Multimodal Queries
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|a Big Data Management and Analytics -- Optimization of Row Pattern Matching over Sequence Data in Spark SQL -- Rainfall Estimation from Traffic Cameras -- Towards Identifying De-Anonymisation Risks in Distributed Health Data Silos -- An Attribute-Based Fine-Grained Access Control Mechanism for HBase -- Data Structures and Data Management -- Lopper: An Efficient Method for Online Log Pattern Mining based on Hybrid Clustering Tree -- Discord Monitoring for Streaming Time-series -- Partially Indexing on Flash Memory -- HGraph: A Connected-Partition Approach to Proximity Graphs for Similarity Search -- Management and Processing of Knowledge -- Statistical Processing of Stopwords on SNS -- Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence -- Probabilistic Algorithm to Predict Missing Facts from Knowledge Graphs -- Semantic Oppositeness Embedding Using an Autoencoder-based Learning Model --
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|a COMET: A Contextualized Molecule-based Matching Technique.-Authenticity, Privacy, Security and Trust -- Differentially Private Non-parametric Machine Learning as a Service -- PURE: A Privacy Aware Rule-Based Framework over Knowledge Graphs -- FFT-2PCA: a new Feature Extraction Method for Data-Based Fault Detection -- Consistency, Integrity, Quality of Data -- ADaQL to Monitor Data Quality in Machine Learning Applications -- Automated Detection and Monitoring of Advanced Data Quality Rules -- Effect of Imprecise Data Income-flow Variability on Harvest Stability: A Quantile-based Approach -- Decision Support Systems -- Fairness-enhancing interventions in stream classification -- Early turnover prediction of new restaurant employees from their attendance records and attributes -- An Efficient Premiumness and Utility-based Itemset Placement Scheme for Retail Stores -- Data Lakes: Trends and Perspectives -- An Efficient Greedy Algorithm for Sequence Recommendation --
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653 |
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|a Artificial Intelligence
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653 |
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|a Database Management
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653 |
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|a Data mining
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653 |
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|a Application software
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653 |
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|a Data protection
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653 |
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|a Artificial intelligence
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653 |
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|a Data Mining and Knowledge Discovery
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653 |
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|a Computer and Information Systems Applications
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653 |
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|a Data and Information Security
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653 |
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|a Database management
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700 |
1 |
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|a Küng, Josef
|e [editor]
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700 |
1 |
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|a Chakravarthy, Sharma
|e [editor]
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700 |
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|a Anderst-Kotsis, Gabriele
|e [editor]
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041 |
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7 |
|a eng
|2 ISO 639-2
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989 |
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|b Springer
|a Springer eBooks 2005-
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490 |
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|a Information Systems and Applications, incl. Internet/Web, and HCI
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|a 10.1007/978-3-030-27615-7
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856 |
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|u https://doi.org/10.1007/978-3-030-27615-7?nosfx=y
|x Verlag
|3 Volltext
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|a 006.312
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|a This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services
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