Search
Search Results
-
Knowledge Graph Completion for Activity Recommendation in Business Process Modeling
Activity recommendation is an approach to assist process modelers by recommending suitable activities to be inserted at a user-defined position. In...
-
Explaining neural networks without access to training data
We consider generating explanations for neural networks in cases where the network’s training data is not accessible, for instance due to privacy or...
-
Rule Confidence Aggregation for Knowledge Graph Completion
Rule learning approaches for knowledge graph completion are efficient, interpretable and competitive to purely neural models. The rule confidence...
-
Reevaluation of Inductive Link Prediction
Within this paper, we show that the evaluation protocol currently used for inductive link prediction is heavily flawed as it relies on ranking the...
-
PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
We present PGTNet, an approach that transforms event logs into graph datasets and leverages graph-oriented data for training Process Graph...
-
Experiencing Data on Location: A Case Study of Visualizing Air Quality for Citizens
Visualizing urban data has different purposes. Besides more traditional goals such as supporting experts to decide on smart city policies, supporting...
-
Planning Landmark Based Goal Recognition Revisited: Does Using Initial State Landmarks Make Sense?
Goal recognition is an important problem in many application domains (e.g., pervasive computing, intrusion detection, computer games, etc.). In many...
-
Comparing Apples and Oranges? On the Evaluation of Methods for Temporal Knowledge Graph Forecasting
Due to its ability to incorporate and leverage time information in relational data, Temporal Knowledge Graph (TKG) learning has become an...
-
Activity Recommendation for Business Process Modeling with Pre-trained Language Models
Activity recommendation in business process modeling is concerned with suggesting suitable labels for a new activity inserted by a modeler in a...
-
Outlying Aspect Mining via Sum-Product Networks
Outlying Aspect Mining (OAM) is the task of identifying a subset of features that distinguish an outlier from normal data, which is important for...
-
Learning Disentangled Discrete Representations
Recent successes in image generation, model-based reinforcement learning, and text-to-image generation have demonstrated the empirical advantages of...
-
Predicting Master’s students’ academic performance: an empirical study in Germany
The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM)...
-
Evaluating the Impact of AI-Based Priced Parking with Social Simulation
Across the world, increasing numbers of cars in urban centers lead to congestion and adverse effects on public health as well as municipal climate...
-
Supervised Knowledge Aggregation for Knowledge Graph Completion
We explore data-driven rule aggregation based on latent feature representations in the context of knowledge graph completion. For a given query and a...
-
Self-learning Governance of Black-Box Multi-Agent Systems
Agents in Multi-Agent Systems (MAS) are not always built and controlled by the system designer, e.g., on electronic trading platforms. In this case,...
-
The state of artificial intelligence: Procurement versus sales and marketing
Procurement, sales and marketing are the main boundary‐spanning functions of an organization – each with a specific focus and partly different views...
-
On the Use of Knowledge Graph Completion Methods for Activity Recommendation in Business Process Modeling
Business process modeling is essential for organisations. However, it is a time-consuming task that requires expert knowledge. In particular, this is...
-
Dynamic Forest for Learning from Data Streams with Varying Feature Spaces
In this paper, we propose a new ensemble method, which is called Dynamic Forest, for learning from data streams with varying feature spaces. Unlike...
-
Arrow R-CNN for handwritten diagram recognition
We address the problem of offline handwritten diagram recognition. Recently, it has been shown that diagram symbols can be directly recognized with...
-
A Rule-Based Recommendation Approach for Business Process Modeling
Business process modeling is a crucial, yet time-consuming and knowledge-intensive task. This is particularly the case when modeling a...