A5080792995- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- Business Process Modeling and Analysis
- Advanced Database Systems and Queries
- AI in Service Interactions
- Big Data and Business Intelligence
- Information Systems Theories and Implementation
- Information Technology Governance and Strategy
- Software Engineering Techniques and Practices
- Knowledge Management and Sharing
- Technology Adoption and User Behaviour
- Personal Information Management and User Behavior
- Web Data Mining and Analysis
- Open Source Software Innovations
- Natural Language Processing Techniques
- Usability and User Interface Design
- ERP Systems Implementation and Impact
- Gaze Tracking and Assistive Technology
- Innovative Human-Technology Interaction
- Digital Innovation in Industries
- Team Dynamics and Performance
- Data Visualization and Analytics
- Digital Marketing and Social Media
- Digital Platforms and Economics
- Software Engineering Research
Karlsruhe Institute of Technology
2016-2025
University of Mannheim
2010-2019
University of Cologne
2019
Georgia State University
2019
Institute for Enterprise Systems
2010-2018
AID Atlanta
2018
University of Groningen
2015
Karlsruhe University of Education
2000-2011
Systems, Applications & Products in Data Processing (United Kingdom)
2010
FZI Research Center for Information Technology
2001-2005
The Semantic Web relies heavily on formal ontologies to structure data for comprehensive and transportable machine understanding. Thus, the proliferation of factors largely in Web's success. authors present an ontology learning framework that extends typical engineering environments by using semiautomatic construction tools. encompasses import, extraction, pruning, refinement evaluation.
Sir Isaac Newton (1676) famously said, “If I have seen further, it is by standing on the shoulders of giants.” Research a collaborative, evolutionary endeavor—and no different with design science research (DSR), which builds upon existing knowledge and creates new to pass future projects. However, despite vast, growing body DSR contributions, scant evidence accumulation evolution has been articulated in an organized knowledge. Most contributions rather stand their own feet than giants, this...
Users are increasingly empowered to personalize natural language interfaces (NLIs) by teaching how handle new (NL) inputs. However, our formative study found that when NL inputs, users require assistance in clarifying ambiguities arise and want insight into which parts of the input NLI understands. In this paper we introduce ONYX, an intelligent agent interactively learns inputs combining programming programming-by-demonstration, also known as multi-modal interactive task learning. To...
Several challenges exist related to applying ontologies in real-world environments. The authors present an integrated enterprise-knowledge management architecture, focusing on how support multiple and manage ontology evolution.
Web services can be defined as loosely coupled, reusable software components that semantically encapsulate discrete functionality and are distributed programmatically accessible over standard Internet protocols. have received a lot of hype, the reasons for which not easily determined. Some their benefits might even seem to waste away, once we touch on nitty-gritty details, because per se do offer solution underlying problems. The contributions included in this section delve into some these...
The success of information systems (IS) development strongly depends on the accuracy requirements gathered from users and other stakeholders. When developing a new IS, about 80 percent these are recorded in informal documents (e.g., interview transcripts or discussion forums) using natural language. However, processing resultant language resources is inherently complex often error prone due to ambiguity, inconsistency, incompleteness. Thus, even highly qualified engineers struggle process...