default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKlaus Turowski
Person information
- affiliation: University of Magdeburg, Faculty of Computer Science, Germany
- affiliation: University of Augsburg, Business Faculty, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j33]Sebastian Rosenkranz
, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Explaining the Business-Technological Age of Legacy Information Systems. IEEE Access 12: 84579-84611 (2024)- [j32]Christian Haertel, Vincent Donat, Daniel Staegemann, Christian Daase, Marco Finkendei, Klaus Turowski:
The Application of Data Science at Original Equipment Manufacturers: A Literature Review. IEEE Access 12: 114584-114600 (2024) - [c205]Christian Haertel, Vincent Donat, Daniel Staegemann, Matthias Pohl, Klaus Turowski:
Challenges in Data Science Project Management: A Case Study in a European OEM. AMCIS 2024 - [c204]Matthias Pohl, Hannah Giegold, Christian Haertel, Daniel Staegemann, Klaus Turowski:
Customer Identity Management in Health Insurance with Blockchain Technology: A Literature Review. BIOSTEC (2) 2024: 803-811 - [c203]Maria Chernigovskaya, Andrey Kharitonov, Abdulrahman Nahhas, Klaus Turowski:
Reinforcement Learning for Hyper-Parameter Optimization in the context of Capacity Management of SAP Enterprise Applications. CoDIT 2024: 294-299 - [c202]Robert Häusler, Daniel Staegemann, Klaus Turowski:
Individual Business Simulation Games as a Service: Towards a Concept for Adaptive ERP Education. CSEDU (1) 2024: 494-501 - [c201]Damanpreet Singh Walia, Ksenia Neumann, Visman Jeet Singh Walia, Malte Rathjens, Stefan Weidner, Klaus Turowski:
Unveiling the Potential: Assessing the Role of SSI Wallets in Promoting Sustainability in Federated Learning Environments. CSEDU (1) 2024: 502-509 - [c200]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Klaus Turowski:
Classifying Design Science Research in Terms of Types of Reasoning from an Epistemological Perspective. DESRIST 2024: 155-167 - [c199]Abdulrahman Nahhas, Andrey Kharitonov, Christian Haertel, Klaus Turowski:
Imitation Learning Based on Deep Reinforcement Learning for Solving Scheduling Problems. HICSS 2024: 1649-1658 - [c198]Christian Haertel, Sarah Schramm, Matthias Pohl, Sascha Bosse, Daniel Staegemann, Christian Daase, Klaus Turowski:
A Methodology for Constructing Patterns for the Management of Data Science Projects. ICEIS (1) 2024: 354-365 - [c197]Christian Daase, Christian Haertel, Klaus Turowski:
Explainable Business Intelligence for Video Analytics in Retail. ICEIS (1) 2024: 784-791 - [c196]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Alexander Zeier, Achim Ramesohl, Klaus Turowski:
On the Current State of Generative Artificial Intelligence: A Conceptual Model of Potentials and Challenges. ICEIS (1) 2024: 845-856 - [c195]Daniel Staegemann, Malte Rathjens, Hannes Hinniger, Vivian Schmidt, Klaus Turowski:
Exploring the Test Driven Development of a Big Data Infrastructure Examining Gun Violence Incidents in the United States of America. ICSBT 2024: 103-114 - [c194]Andrey Kharitonov, Amro Abdalla, Abdulrahman Nahhas, Daniel Gunnar Staegemann, Christian Haertel, Christian Daase, Klaus Turowski:
A Literature Survey on Pitfalls of Open-Source Dependency Management in Enterprise. ICSOFT 2024: 15-22 - [c193]Christian Daase, Daniel Staegemann, Klaus Turowski:
Overcoming the Complexity of Quality Assurance for Big Data Systems: An Examination of Testing Methods. IoTBDS 2024: 358-369 - [c192]Matthias Volk, Daniel Staegemann, Muralidhar Kuluru, Eugen Martel, Klaus Turowski:
A Low-Cost Autograder Approach utilizing Serverless Cloud Technologies for Higher Educational Institutions (HEI). PACIS 2024 - 2023
- [j31]Christian Daase, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Creation of a Framework and a Corresponding Tool Enabling the Test-Driven Development of Microservices. J. Softw. 18(2): 55-69 (2023) - [j30]Tobias Altenburg, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Reliability Estimation and Optimization of a Smart Meter Architecture Using a Monte Carlo Simulation. SN Comput. Sci. 4(5): 438 (2023) - [c191]Matthias Pohl, Christian Haertel, Daniel Staegemann, Klaus Turowski:
The Linkage to Business Goals in Data Science Projects. ACIS 2023 - [c190]Christian Haertel, Matthias Pohl, Abdulrahman Nahhas, Daniel Staegemann, Klaus Turowski:
A Survey of Technology Selection Approaches in Data Science Projects. AMCIS 2023 - [c189]Matthias Pohl, Christian Haertel, Daniel Staegemann, Klaus Turowski:
Data Valuation Methods - A Literature Review. AMCIS 2023 - [c188]Daniel Staegemann, Matthias Volk, Matthias Pohl, Christian Haertel, Naoum Jamous, Klaus Turowski:
Achieving Competitive Advantages Through Situation-Aware Big Data Engineering - When (Not) to Use Test Driven Development. AMCIS 2023 - [c187]Christian Haertel, Daniel Staegemann, Christian Daase, Matthias Pohl, Abdulrahman Nahhas, Klaus Turowski:
MLOps in Data Science Projects: A Review. IEEE Big Data 2023: 2396-2404 - [c186]Matthias Pohl, Christian Haertel, Klaus Turowski:
Value Creation from Data Science Applications - A Literature Review. BIR 2023: 327-338 - [c185]Andrey Kharitonov, Abdulrahman Nahhas, Hendrik Müller, Klaus Turowski:
Data Driven Meta-Heuristic-Assisted Approach for Placement of Standard IT Enterprise Systems in Hybrid-Cloud. CLOSER 2023: 139-146 - [c184]Maria Chernigovskaya, Andrey Kharitonov, Klaus Turowski:
A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms. CLOSER 2023: 236-243 - [c183]Christian Daase, Klaus Turowski:
Conducting Design Science Research in Society 5.0 - Proposal of an Explainable Artificial Intelligence Research Methodology. DESRIST 2023: 250-265 - [c182]Abhijith Remesh, Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
A Hybrid Job Scheduling Approach on Cloud Computing Environments on the Usage of Heuristics and Metaheuristics Methods. HICSS 2023: 1580-1589 - [c181]Andrey Kharitonov, Roheet Rajendran, Hendrik Müller, Klaus Turowski:
Utility of Univariate Forecasting for Workload Metrics Predictions in Enterprise Applications. KMIS 2023: 231-240 - [c180]Christian Haertel, Christian Daase, Daniel Staegemann, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Toward Standardization and Automation of Data Science Projects: MLOps and Cloud Computing as Facilitators. KMIS 2023: 294-302 - [c179]Matthias Pohl, René Degenkolbe, Daniel Gunnar Staegemann, Klaus Turowski:
Decentralised Autonomous Management of an Association Through Smart Contracts According to German Legislation. ICEIS (1) 2023: 212-218 - [c178]Christian Daase, Matthias Volk, Daniel Staegemann, Klaus Turowski:
The Future of Commerce: Linking Modern Retailing Characteristics with Cloud Computing Capabilities. ICEIS (2) 2023: 418-430 - [c177]Daniel Staegemann, Christian Haertel, Christian Daase, Matthias Pohl, Klaus Turowski:
A Meta-Review on the Use of Artificial Intelligence in the Context of Electrical Power Grid Operators. ICINCO (1) 2023: 335-341 - [c176]Christian Daase, Anuraag Pandey, Daniel Staegemann, Klaus Turowski:
Sustainability in Robotic Process Automation: Proposing a Universal Implementation Model. ICINCO (1) 2023: 770-779 - [c175]Daniel Staegemann, Matthias Volk, Mohammad Abdallah, Klaus Turowski:
Towards the Application of Test Driven Development in Big Data Engineering. ICIT 2023: 163-167 - [c174]Robert Häusler, Malte Rathjens, Daniel Staegemann, Klaus Turowski:
Towards an Evaluation Concept for Business Simulation Games: Preliminary Work and Piloting in SAP ERP Teaching. ICSBT 2023: 94-103 - [c173]Daniel Staegemann, Sujith Sudhakaran, Christian Daase, Klaus Turowski:
Exploring the Test Driven Development of an Information Retrieval System. ICSBT 2023: 104-113 - [c172]Daniel Staegemann, Matthias Volk, Mohammad Abdallah, Klaus Turowski:
On the Challenges of Applying Test Driven Development to the Engineering of Big Data Applications. ICSBT 2023: 129-135 - [c171]Tobias Altenburg, Daniel Staegemann, Klaus Turowski:
Identifying the Economic Relevance of Smart Meter Reliability in Germany: A Cost-Benefit Analysis. ICSBT 2023: 203-208 - [c170]Christian Daase, Daniel Staegemann, Anastasija Nikiforova, Victor Chang, Johannes Hintsch, Matthias Volk, Klaus Turowski:
Towards the Creation of a Holistic Video Analytics Platform for Retail Environments. ICSBT 2023: 216-225 - [c169]Daniel Staegemann, Natalie Schröder, Christian Daase, Christian Haertel, Matthias Pohl, Robert Häusler, Johannes Hintsch, Klaus Turowski:
Contrasting the Necessary Skills of Leaders in Classical and Agile Software Development. ISD 2023 - [c168]Abdulrahman Nahhas, Christian Haertel, Christian Daase, Matthias Volk, Achim Ramesohl, Heiko Steigerwald, Alexander Zeier, Klaus Turowski:
On the Integration of Google Cloud and SAP HANA for Adaptive Supply Chain in Retailing. ISM 2023: 1857-1866 - [c167]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Matthias Volk, Heiko Steigerwald, Achim Ramesohl, Bernd Schneider, Alexander Zeier, Klaus Turowski:
Following the Digital Thread - A Cloud-Based Observation. ISM 2023: 1867-1876 - [c166]Daniel Staegemann, Matthias Pohl, Christian Haertel, Christian Daase, Mohammad Abdallah, Klaus Turowski:
An Overview of the Approaches for Generating Test Data in the Context of the Quality Assurance of Big Data Applications. SITIS 2023: 30-37 - [c165]Ksenia Neumann, Damanpreet Singh Walia, Daniel Staegemann, Robert Häusler, Stefan Weidner, Klaus Turowski:
Towards a German National Education Platform. SoftCOM 2023: 1-6 - 2022
- [j29]Daniel Staegemann, Matthias Volk, Maneendra Perera, Christian Haertel, Matthias Pohl, Christian Daase, Klaus Turowski:
A Literature Review on the Challenges of Applying Test-Driven Development in Software Engineering. Complex Syst. Informatics Model. Q. 31: 18-28 (2022) - [j28]Hendrik Müller, Andrey Kharitonov, Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski:
Addressing IT Capacity Management Concerns Using Machine Learning Techniques. SN Comput. Sci. 3(1): 26 (2022) - [c164]Abhijith Remesh, Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
Investigating different optimization criteria for a hybrid job scheduling approach based on heuristics and metaheuristics. ACIS 2022: 48 - [c163]Christian Haertel, Abdulrahman Nahhas, Christian Daase, Matthias Volk, Klaus Turowski:
A Holistic View of Adaptive Supply Chain in Retailing Industry. AMCIS 2022 - [c162]Matthias Pohl, Daniel Gunnar Staegemann, Klaus Turowski:
The Performance Benefit of Data Analytics Applications. ANT/EDI40 2022: 679-683 - [c161]Christian Haertel, Matthias Pohl, Daniel Staegemann, Klaus Turowski:
Project Artifacts for the Data Science Lifecycle: A Comprehensive Overview. IEEE Big Data 2022: 2645-2654 - [c160]Daniel Staegemann, René Degenkolbe, Stefan Weidner, Robert Häusler, Vinzent Lange, Klaus Turowski:
Possible Application Scenarios for a German National Education Platform. CSEDU (1) 2022: 361-368 - [c159]Sven Timmermann, Daniel Staegemann, Matthias Volk, Matthias Pohl, Christian Haertel, Johannes Hintsch, Klaus Turowski:
Facilitating the Decentralisation of Software Development Projects from a Project Management Perspective: A Literature Review. FEMIB 2022: 22-34 - [c158]Matthias Volk, Daniel Staegemann, Ashraful Islam, Klaus Turowski:
Facing Big Data System Architecture Deployments: Towards an Automated Approach Using Container Technologies for Rapid Prototyping. HICSS 2022: 1-10 - [c157]Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
Deep Reinforcement Learning Techniques For Solving Hybrid Flow Shop Scheduling Problems: Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C). HICSS 2022: 1-10 - [c156]Daniel Staegemann, Matthias Volk, Maneendra Perera, Klaus Turowski:
Exploring the Test Driven Development of a Fraud Detection Application using the Google Cloud Platform. KDIR 2022: 83-94 - [c155]Daniel Staegemann, Matthias Volk, Naoum Jamous, Klaus Turowski:
A Process Model for Test Driven Development in the Big Data Domain. KDIR 2022: 109-118 - [c154]Matthias Volk, Daniel Staegemann, Klaus Turowski:
Providing Clarity on Big Data: Discussing Its Definition and the Most Relevant Data Characteristics. KDIR 2022: 141-148 - [c153]Azeem Lodhi, Gunter Saake, Klaus Turowski:
Empirical Evaluation of BPMN Extension Language. KDIR 2022: 239-247 - [c152]Matthias Volk, Daniel Staegemann, Akanksha Saxena, Johannes Hintsch, Naoum Jamous, Klaus Turowski:
Lowering Big Data Project Barriers: Identifying System Architecture Templates for Standard Use Cases in Big Data. ICSBT 2022: 33-44 - [c151]Daniel Staegemann, Matthias Volk, Klaus Turowski:
Adapting the (Big) Data Science Engineering Process to the Application of Test Driven Development. ICSBT 2022: 120-129 - [c150]Tobias Altenburg, Matthias Volk, Daniel Staegemann, Klaus Turowski:
Reliability Estimation of a Smart Metering Architecture using a Monte Carlo Simulation. IoTBDS 2022: 47-54 - [c149]Daniel Staegemann, Matthias Volk, Priyanka Byahatti, Nikhilkumar Italiya, Suhas Shantharam, Apoorva Byaladakere Chandrashekar, Klaus Turowski:
Implementing Test Driven Development in the Big Data Domain: A Movie Recommendation System as an Exemplary Case. IoTBDS 2022: 239-248 - [c148]Christian Haertel, Matthias Pohl, Abdulrahman Nahhas, Daniel Staegemann, Klaus Turowski:
Toward A Lifecycle for Data Science: A Literature Review of Data Science Process Models. PACIS 2022: 242 - 2021
- [j27]Daniel Staegemann, Matthias Volk, Aamir Shakir, Erik Lautenschläger, Klaus Turowski:
Examining the Interplay Between Big Data and Microservices - A Bibliometric Review. Complex Syst. Informatics Model. Q. 27: 87-118 (2021) - [j26]Daniel Staegemann, Matthias Volk, Klaus Turowski:
Quality Assurance in Big Data Engineering - A Metareview. Complex Syst. Informatics Model. Q. 28: 1-14 (2021) - [j25]Christian Haertel, Matthias Pohl, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Methodological Case Study Approach for Detecting Business Model Enablers in Copycat Ventures. Int. J. Organ. Collect. Intell. 11(4): 35-54 (2021) - [c147]Johannes Hintsch, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Low-code Development Platform Usage: Towards Bringing Citizen Development and Enterprise IT into Harmony. ACIS 2021: 11 - [c146]Matthias Volk, Daniel Staegemann, Dennis Bischoff, Klaus Turowski:
Applying Multi-Criteria Decision-Making for the Selection of Big Data Technologies. AMCIS 2021 - [c145]Aamir Shakir, Daniel Staegemann, Matthias Volk, Naoum Jamous, Klaus Turowski:
Towards a Concept for Building a Big Data Architecture with Microservices. BIS 2021: 83-94 - [c144]Daniel Staegemann, Hannes Feuersenger, Matthias Volk, Patrick Liedtke, Hans-Knud Arndt, Klaus Turowski:
Investigating the Incorporation of Big Data in Management Information Systems. BIS (Workshops) 2021: 109-120 - [c143]Daniel Staegemann, Matthias Volk, Erik Lautenschläger, Matthias Pohl, Mohammad Abdallah, Klaus Turowski:
Applying Test Driven Development in the Big Data Domain - Lessons From the Literature. ICIT 2021: 511-516 - [c142]Robert Häusler, Marcus Tröger, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Towards a Systematic Requirements Engineering for IT System-based Business Simulation Games. CSEDU (1) 2021: 386-391 - [c141]Abdulrahman Nahhas, Jahnavi Thimmaiah Cheyyanda, Klaus Turowski:
An adaptive scheduling framework for the dynamic virtual machines placement to reduce energy consumption in cloud data centers. HICSS 2021: 1-10 - [c140]Abdulrahman Nahhas, Marco Krist, Klaus Turowski:
An adaptive scheduling framework for solving multi-objective hybrid flow shop scheduling problems. HICSS 2021: 1-10 - [c139]Daniel Staegemann, Matthias Volk, Christian Daase, Matthias Pohl, Klaus Turowski:
A Concept for the Use of Chatbots to Provide the Public with Vital Information in Crisis Situations. ICICT (2) 2021: 281-289 - [c138]Daniel Staegemann, Matthias Volk, Akanksha Saxena, Matthias Pohl, Abdulrahman Nahhas, Robert Häusler, Mohammad Abdallah, Sascha Bosse, Naoum Jamous, Klaus Turowski:
Challenges in Data Acquisition and Management in Big Data Environments. IoTBDS 2021: 193-204 - [c137]Daniel Staegemann, Matthias Volk, Matthias Pohl, Robert Häusler, Abdulrahman Nahhas, Mohammad Abdallah, Klaus Turowski:
A Preliminary Overview of the Situation in Big Data Testing. IoTBDS 2021: 296-302 - [c136]Andrey Kharitonov, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Comparative analysis of machine learning models for anomaly detection in manufacturing. ISM 2021: 1288-1297 - [c135]Abdulrahman Nahhas, Andrey Kharitonov, Ahmad Alwadi, Klaus Turowski:
Hybrid Approach for Solving Multi-Objective Hybrid Flow Shop Scheduling Problems with Family Setup Times. ISM 2021: 1685-1694 - 2020
- [j24]Matthias Volk, Daniel Staegemann, Ivayla Trifonova, Sascha Bosse, Klaus Turowski:
Identifying Similarities of Big Data Projects-A Use Case Driven Approach. IEEE Access 8: 186599-186619 (2020) - [j23]Daniel Staegemann, Matthias Volk, Christian Daase, Klaus Turowski:
Discussing Relations Between Dynamic Business Environments and Big Data Analytics. Complex Syst. Informatics Model. Q. 23: 58-82 (2020) - [j22]Matthias Volk, Daniel Staegemann, Naoum Jamous, Matthias Pohl, Klaus Turowski:
Providing Clarity on Big Data Technologies: The BDTOnto Ontology. Int. J. Intell. Inf. Technol. 16(2): 49-73 (2020) - [c134]Christian Daase, Daniel Staegemann, Matthias Volk, Abdulrahman Nahhas, Klaus Turowski:
Automation of Customer Initiated Back Office Processes: A Design Science Research Approach to link Robotic Process Automation and Chatbots. ACIS 2020: 15 - [c133]Daniel Staegemann, Matthias Volk, Naoum Jamous, Klaus Turowski:
Exploring the Applicability of Test Driven Development in the Big Data Domain. ACIS 2020: 37 - [c132]Matthias Pohl, René Degenkolbe, Daniel Staegemann, Klaus Turowski:
Towards a Blockchain Technology Framework - Literature Review on components in blockchain implementations. ACIS 2020: 48 - [c131]Daniel Staegemann, Matthias Volk, Naoum Jamous, Ranjan Venkatesh, Stefan Willi Hart, Sascha Bosse, Klaus Turowski:
Improving the Quality Validation of the ETL Process using Test Automation. AMCIS 2020 - [c130]Matthias Volk, Daniel Staegemann, Felix Prothmann, Klaus Turowski:
Towards an Automatized Way for Modeling Big Data System Architectures. BIS 2020: 46-60 - [c129]Robert Häusler, Daniel Staegemann, Matthias Volk, Sascha Bosse, Christian Bekel, Klaus Turowski:
Generating Content-Compliant Training Data in Big Data Education. CSEDU (1) 2020: 104-110 - [c128]Philipp Stecher, Matthias Pohl, Klaus Turowski:
Enterprise architecture's effects on organizations' ability to adopt artificial intelligence - A Resource-based perspective. ECIS 2020 - [c127]Christian Haertel, Matthias Pohl, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Comparative Study of e-Commerce Ventures: Copycat Enablers in Business Models. FEMIB 2020: 80-90 - [c126]Matthias Pohl, Ali Hashaam, Sascha Bosse, Daniel Gunnar Staegemann, Matthias Volk, Frederik Kramer, Klaus Turowski:
Application of NLP to determine the State of Issues in Bug Tracking Systems. ICDM (Workshops) 2020: 53-61 - [c125]Tobias Altenburg, Sascha Bosse, Klaus Turowski:
Safety in Distributed Sensor Networks: A Literature Review. IoTBDS 2020: 161-168 - [c124]Daniel Staegemann, Matthias Volk, Alexandra Grube, Johannes Hintsch, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Classifying Big Data Taxonomies: A Systematic Literature Review. IoTBDS 2020: 267-278 - [c123]Matthias Volk, Daniel Staegemann, Sascha Bosse, Robert Häusler, Klaus Turowski:
Approaching the (Big) Data Science Engineering Process. IoTBDS 2020: 428-435 - [c122]Daniel Staegemann, Matthias Volk, Tuan Vu, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Determining Potential Failures and Challenges in Data Driven Endeavors: A Real World Case Study Analysis. IoTBDS 2020: 453-460 - [c121]Matthias Volk, Daniel Staegemann, Sascha Bosse, Abdulrahman Nahhas, Klaus Turowski:
Towards a Decision Support System for Big Data Projects. Wirtschaftsinformatik (Zentrale Tracks) 2020: 357-368 - [c120]Sascha Bosse, Abdulrahman Nahhas, Klaus Turowski:
Quantitative Analysis of the Effects of Different Carbon Tax Levels on Emissions and Costs of Data Centers. Wirtschaftsinformatik (Zentrale Tracks) 2020: 1349-1363
2010 – 2019
- 2019
- [j21]Junjie Song, Naoum Jamous, Klaus Turowski:
A dynamic perspective: local interactions driving the spread of social networks. Enterp. Inf. Syst. 13(2): 219-235 (2019) - [c119]Ahmad Alwadi, Abdulrahman Nahhas, Sascha Bosse, Naoum Jamous, Klaus Turowski:
A Modernized Model for Performance Requirements and Their Interdependencies. AICCSA 2019: 1-8 - [c118]Robert Häusler, Chris Bernhardt, Sascha Bosse, Klaus Turowski:
A Review of the Literature on Teaching and Learning Environments. AMCIS 2019 - [c117]Jesse Roberts, Matthias Volk, Robert Neumann, Klaus Turowski:
Machine Learning Techniques for Annotations of Large Financial Text Datasets. AMCIS 2019 - [c116]Daniel Staegemann, Matthias Volk, Naoum Jamous, Klaus Turowski:
Understanding Issues in Big Data Applications - A Multidimensional Endeavor. AMCIS 2019 - [c115]Matthias Volk, Sascha Bosse, Dennis Bischoff, Klaus Turowski:
Decision-Support for Selecting Big Data Reference Architectures. BIS (1) 2019: 3-17 - [c114]Johannes Hintsch, Klaus Turowski:
Enterprise Computing: A Case Study on Current Practices in SAP Operations. BIS (Workshops) 2019: 124-135 - [c113]Daniel Staegemann, Matthias Volk, Christian Lucht, Christian Klie, Michael Hintze, Klaus Turowski:
An Inventory-Based Mobile Application for Warehouse Management to Digitize Very Small Enterprises. BIS (2) 2019: 257-268 - [c112]Abdulrahman Nahhas, Sascha Bosse, Matthias Pohl, Klaus Turowski:
Toward an Autonomic and Adaptive Load Management Strategy for Reducing Energy Consumption under Performance Constraints in Data Centers. CLOSER 2019: 471-478 - [c111]Matthias Pohl, Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski:
Proof of Provision: Improving Blockchain Technology by Cloud Computing. CLOSER 2019: 523-527 - [c110]Sascha Bosse, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Towards an Automated Optimization-as-a-Service Concept. IoTBDS 2019: 339-343 - [c109]Matthias Volk, Daniel Staegemann, Matthias Pohl, Klaus Turowski:
Challenging Big Data Engineering: Positioning of Current and Future Development. IoTBDS 2019: 351-358 - [c108]Hendrik Müller, Sascha Bosse, Klaus Turowski:
On the Utility of Machine Learning for Service Capacity Management of Enterprise Applications. SITIS 2019: 274-281 - [c107]Daniel Staegemann, Matthias Volk,