New Trends in Databases and Information Systems 1st edition by Tatjana Welzer , Johann Eder, Vili Podgorelec, Robert Wrembel, Mirjana Ivanovic, Johann Gamper, Mikoƚaj Morzy, Theodoros Tzouramanis, Jerome Darmont ISBN 3030302776 9783030302771

ADBIS 2019 Short Papers

1. Distributed Computation of Top-k Degrees in Hidden Bipartite Graphs

   • Focuses on efficient computation techniques for top-k degrees in hidden bipartite graphs.

2. Applying Differential Evolution with Threshold Mechanism for Feature Selection on a Phishing Websites Classification

   • Introduces differential evolution with a threshold mechanism for feature selection in phishing website detection.

3. Document Data Modeling: A Conceptual Perspective

   • Discusses a conceptual approach to document data modeling in information systems.

4. Towards Automated Visualisation of Scientific Literature

   • Aims at automating the process of visualizing scientific literature for enhanced accessibility and understanding.

5. Metadata Management for Data Lakes

   • Examines the importance of metadata management in the context of large-scale data lakes.

6. Correlation Between Students’ Background and the Knowledge on Conceptual Database Modelling

   • Investigates how students’ background correlates with their understanding of conceptual database modeling.

7. Smart Caching for Efficient Functional Dependency Discovery

   • Proposes a smart caching method to improve the efficiency of functional dependency discovery.

8. The Agents’ Selection Methods for a Consensus-Based Investment Strategy in a Multi-agent Financial Decisions Support System

   • Discusses agent selection strategies for decision-making in multi-agent systems focused on financial support.

9. Ratings vs. Reviews in Recommender Systems: A Case Study on the Amazon Movies Dataset

   • Explores the differences and impact of ratings versus reviews in movie recommender systems.

10. Solution Pattern for Anomaly Detection in Financial Data Streams

    • Introduces a solution pattern to detect anomalies in financial data streams for better analysis.

11. Exploring Pattern Mining for Solving the Ontology Matching Problem

    • Investigates the application of pattern mining techniques to solve the ontology matching problem.

12. Systematic Creation of Cumulative Design Science Research Knowledge with a Case Study in the Field of Automatic Speech Recognition

    • Focuses on the creation of cumulative knowledge in design science research with a case study on speech recognition.

13. SLFTD: A Subjective Logic-Based Framework for Truth Discovery

    • Proposes a subjective logic-based framework to improve truth discovery in data analysis.

14. A Cellular Network Database for Fingerprint Positioning Systems

    • Discusses the design and usage of a database for positioning systems based on cellular network fingerprints.

15. Automatically Configuring Parallelism for Hybrid Layouts

    • Focuses on automating the configuration of parallelism in hybrid layouts for improved performance.

16. Automated Vertical Partitioning with Deep Reinforcement Learning

    • Introduces deep reinforcement learning for automating vertical partitioning in database systems.

17. BrainFlux: An Integrated Data Warehousing Infrastructure for Dynamic Health Data

    • Proposes an integrated data warehousing solution tailored for dynamic health data management.

18. Modelling and Querying Star and Snowflake Warehouses Using Graph Databases

    • Explores the use of graph databases to model and query star and snowflake data warehouses.

19. Towards Integrating Collaborative Filtering in Visual Data Exploration Systems

    • Investigates the integration of collaborative filtering techniques into visual data exploration systems.

ADBIS 2019 Workshops

Workshop: Modelling is Going to Become Programming – M2P

1. Usage Models Mapped to Programs

   • Discusses how usage models can be translated into programs, facilitating better software development practices.

2. Phenomenological Framework for Model-Enabled Enterprise Information Systems

   • Proposes a phenomenological framework for integrating models into enterprise information systems.

3. Query-Based Reverse Engineering of Graph Databases – From Program to Model

   • Focuses on reverse engineering techniques for graph databases, converting programs into models.

4. A Model-Driven Needs-Based Augmented Reality: From Model to Program

   • Examines the role of model-driven approaches in creating needs-based augmented reality applications.

5. Graphical E-Commerce Values Filtering Model in Spatial Database Framework

   • Develops a filtering model for e-commerce values in a spatial database context.

6. Transforming Object-Oriented Model to a Web Interface Using XSLT

   • Explores transforming object-oriented models into web interfaces using XSLT (Extensible Stylesheet Language Transformations).

7. Abstract Layers and Generic Elements as a Basis for Expressing Multidimensional Software Knowledge

   • Discusses the use of abstract layers and generic elements to express multidimensional knowledge in software.

8. Model Suite and Model Set in Software Development

   • Investigates the use of model suites and sets in software development for improved design and implementation.

9. Automatic Code Generator for Screen-Based Systems

   • Proposes a tool for automatically generating code for screen-based systems.

10. Formalizing Requirement Specifications for Problem Solving in a Research Domain

    • Focuses on formalizing requirements for problem-solving in specific research domains.

Workshop: Modern Approaches in Data Engineering and Information System Design – MADEISD

1. Customer Value Prediction in Direct Marketing Using Hybrid Support Vector Machine Rule Extraction Method

   • Applies hybrid support vector machine rule extraction for customer value prediction in marketing.

2. Crowd Counting à la Bourdieu

   • Investigates methods for crowd counting, drawing inspiration from Bourdieu’s sociological theories.

3. A Holistic Decision-Making Framework for a Vehicle Sharing System

   • Proposes a decision-making framework to optimize vehicle-sharing systems.

4. Residual MobileNets

   • Discusses the application of residual networks in MobileNets for enhanced performance.

5. A Blockchain-Based Decentralized Self-Balancing Architecture for the Web of Things

   • Introduces a decentralized, blockchain-based self-balancing architecture for the Web of Things.

6. A Business-Context-Based Approach for Message Standards Use – A Validation Study

   • Presents a business-context-based approach for utilizing message standards, validated through case studies.

7. A Two-Tiered Database Design Based on Core Components Methodology

   • Proposes a two-tiered database design methodology based on core components.

Workshop: Semantics in Big Data Management – SemBDM and Data-Driven Process Discovery and Analysis – SIMPDA

1. Using Rule and Goal-Based Agents to Create Metadata Profiles

   • Focuses on using agents for generating metadata profiles based on rules and goals.

2. On Metadata Support for Integrating Evolving Heterogeneous Data Sources

   • Discusses metadata support for integrating diverse and evolving data sources.

3. The Impact of Event Log Subset Selection on the Performance of Process Discovery Algorithms

   • Explores how the selection of event log subsets affects the performance of process discovery algorithms.

4. Exploiting Event Log Event Attributes in RNN-Based Prediction

   • Investigates the use of recurrent neural networks (RNN) in predicting based on event log attributes.

5. Design and Implementation of a Graph-Based Solution for Tracking Manufacturing Products

   • Proposes a graph-based solution for tracking manufacturing products throughout the supply chain.

Workshop: International Workshop on BI and Big Data Applications – BBIGAP

1. An XML Interchange Format for ETL Models

   • Discusses an XML format for exchanging ETL (Extract, Transform, Load) models between systems.

2. Metadata Systems for Data Lakes: Models and Features

   • Explores metadata systems tailored for data lakes, including key models and features.

3. A Metadata Framework for Data Lagoons

   • Proposes a metadata framework for managing large-scale data lagoons.

4. Assessing the Role of Temporal Information in Modelling Short-Term Air Pollution Effects Based on Traffic and Meteorological Conditions: A Case Study in Wrocław

   • Investigates the role of temporal data in modeling short-term air pollution effects, using Wrocław as a case study.

5. Extreme Climate Event Detection Through High Volume of Transactional Consumption Data

   • Focuses on detecting extreme climate events through the analysis of large-scale transactional consumption data.

Workshop: International Workshop on Qualitative Aspects of User-Centered Analytics – QAUCA

1. Data Quality Alerting Model for Big Data Analytics

   • Develops a model for alerting on data quality issues in big data analytics.

2. Framework for Assessing the Smartness Maturity Level of Villages

   • Introduces a framework to assess the “smartness” maturity of villages based on various metrics.

3. GameRecs: Video Games Group Recommendations

   • Focuses on a recommender system for video game recommendations based on group preferences.

4. FIFARecs: A Recommender System for FIFA18

   • Discusses a specific recommender system for FIFA18, focusing on personalized recommendations.

ADBIS 2019 Doctoral Consortium

1. Algorithms and Architecture for Managing Evolving ETL Workflows

   • Research on managing ETL workflows and their evolution over time.

2. Data Integration of Legacy ERP System Based on Ontology Learning from SQL Scripts

   • Investigates integrating legacy ERP systems using ontology learning techniques from SQL scripts.

3. Business Intelligence & Analytics Applied to Public Housing

   • Discusses the application of business intelligence and analytics in public housing management.

4. Textual Data Analysis from Data Lakes

   • Explores methods for analyzing textual data stored in data lakes.

5. A Dockerized String Analysis Workflow for Big Data

   • Introduces a Dockerized workflow for string analysis in big data environments.