A5062035687- Advanced Database Systems and Queries
- Semantic Web and Ontologies
- Data Management and Algorithms
- Data Quality and Management
- Web Data Mining and Analysis
- Topic Modeling
- Natural Language Processing Techniques
- Service-Oriented Architecture and Web Services
- Business Process Modeling and Analysis
- Big Data and Business Intelligence
- Algorithms and Data Compression
- Explainable Artificial Intelligence (XAI)
- Geographic Information Systems Studies
- Machine Learning in Healthcare
- Spam and Phishing Detection
- Machine Learning and Data Classification
- Biomedical Text Mining and Ontologies
- Distributed and Parallel Computing Systems
- AI in cancer detection
- Caching and Content Delivery
- Distributed systems and fault tolerance
- Human Mobility and Location-Based Analysis
- 3D Surveying and Cultural Heritage
- Remote Sensing and LiDAR Applications
- Scientific Computing and Data Management
University of Twente
2015-2025
University of Konstanz
2003
Relational XQuery systems try to re-use mature relational data management infrastructures create fast and scalable XML database technology. This paper describes the main features, key contributions, lessons learned while implementing such a system. Its architecture consists of (i) range-based encoding documents into tables, (ii) compilation technique that translates basic algebra, (iii) restricted (order) property-aware peephole query optimization strategy, (iv) mapping from update...
Interpretable methods based on prototypical patches recognize various components in an image order to explain their reasoning humans. However, existing prototype-based can learn prototypes that are not line with human visual perception, i.e., the same prototype refer different concepts real world, making interpretation intuitive. Driven by principle of explainability-by-design, we introduce PIP-Net (Patch-based Intuitive Prototypes Network): interpretable classification model learns parts a...
This article is a proposal for database index structure, the XPath accelerator , that has been specifically designed to support evaluation of path expressions. As such, capable all axes (including ancestor, following, preceding-sibling, descendant-or-self, etc.). feature lets stand out among related work on XML indexing structures which had focus child and descendant only. The with close eye semantics as well desire engineer its internals so it can be supported by existing relational query...
In mobile and ambient environments, devices need to become autonomous, managing resolving problems without interference from a user. The database of (mobile) device can be seen as its knowledge about objects in the 'real world'. Data exchange between small and/or large computing used supplement update this whenever connection gets established. many situations, however, data different sources referring same real world objects, may conflict. It is task management system resolve such conflicts...
The Web of Things (WoT) enables information gathered by sensors deployed in urban environments to be easily shared utilizing open standards and semantic technologies, creating easier integration with other Web-based information, towards advanced knowledge. Besides WoT, an essential aspect understanding dynamic systems is artificial intelligence (AI). Via AI, data produced WoT-enabled sensory observations can analyzed transformed into meaningful which describes predicts current future...
This study examines how different filming techniques can enhance the quality of 3D reconstructions with a particular focus on their use in indoor crime scene investigations. Using Neural Radiance Fields (NeRF) and Gaussian Splatting, we explored factors like camera orientation, speed, data layering, scanning path affect detail clarity reconstructions. Through experiments mock apartment, identified optimal methods that reduce noise artifacts, delivering clearer more accurate Filming landscape...
A Language Model is a term that encompasses various types of models designed to understand and generate human communication. Large Models (LLMs) have gained significant attention due their ability process text with human-like fluency coherence, making them valuable for wide range data-related tasks fashioned as pipelines. The capabilities LLMs in natural language understanding generation, combined scalability, versatility, state-of-the-art performance, enable innovative applications across...
Relational query processors are probably the best understood (as well as engineered) engines available today. Although carefully tuned to process instances of relational model (tables tuples), these can also provide a foundation for evaluation alien (non-relational) languages: if encoding data and its associated language is given, RDBMS may act like special-purpose processor new language.
Driving is an activity that requires considerable alertness. Insufficient attention, imperfect perception, inadequate information processing, and sub-optimal arousal are possible causes of poor human performance. Understanding these the implementation effective remedies key importance to increase traffic safety improve driver's well-being. For this purpose, we used deep learning algorithms detect level, namely, under-aroused, normal over-aroused for professional truck drivers in a simulated...
Optimization of complex XQueries combining many XPath steps and joins is currently hindered by the absence good cardinality estimation cost models for XQuery. Additionally, state-of-the-art even relational query optimization still struggles to cope with model errors that increase plan size, as well effect correlated selections.
The rapid growth in IT the last two decades has led to a amount of information available online. A new style for sharing is social media. Social media continuously instantly updated source information. In this position paper, we propose framework Information Extraction (IE) from unstructured user generated contents on proposes solutions overcome IE challenges domain such as short context, noisy sparse and uncertain contents. To facing media, State-Of-The-Art approaches need be adapted suit...
Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine from multiple autonomous probabilistic databases, an integration of has be performed. Until now, however, approaches focused on the certain source (relational or XML). There is no work so far. In this paper, we present a first step towards concise consolidation We focus duplicate detection as representative and essential in process. techniques for identifying...
Abstract Data interoperability encompasses the many data management activities needed for effective information in anyone´s or any organization´s everyday work such as cleaning, coupling, fusion, mapping, and extraction. It is our conviction that a significant amount of money time IT devoted to these activities, about dealing with one problem: “semantic uncertainty”. Sometimes subjective, incomplete, not current, incorrect, sometimes it can be interpreted different ways, etc. In opinion,...
In current research and practice, deduplication is usually considered as a deterministic approach in which database tuples are either declared to be duplicates or not. ambiguous situations, however, it often not completely clear-cut, represent the same real-world entity. approaches, many realistic possibilities may ignored, turn can lead false decisions. this article, we present an indeterministic for by using probabilistic target model including techniques proper interpretation of...
Share on Deep web entity monitoring Authors: Mohamamdreza Khelghati University of Twente, Enscehde, Netherlands NetherlandsView Profile , Djoerd Hiemstra Enschede, Maurice Van Keulen Authors Info & Claims WWW '13 Companion: Proceedings the 22nd International Conference World Wide WebMay 2013 Pages 377–382https://doi.org/10.1145/2487788.2487946Online:13 May 2013Publication History 8citation248DownloadsMetricsTotal Citations8Total Downloads248Last 12 Months6Last 6 weeks0 Get Citation AlertsNew...