The quality of a software system highly depends on its architectural design. High quality software systems typically apply expert design experience which has been captured as design patterns. As demonstrated solutions to recurring problems, design patterns help to reuse expert experience in software system design. They have been extensively applied in industry. Mining the instances of design pa...

High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery of optical materials enables advancements in solar energy and other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, and we present an automated Tauc analysis algorithm for...

Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. Such a comparison can offer insight on the val...

This paper describes our experiences with sequence learning activities for intelligent 3D practice environments. An intelligent practice environment offers learning by doing and learning by discovery in a realistic practice situation. A Knowledge-Based-System (KBS) improves learning opportunities with dynamic advice and feedback. An expert system monitors user interactions to provide dynamic ad...

Knowledge-based support vector machines (KBSVMs) incorporate advice from domain experts, which can improve generalization significantly. A major limitation that has not been fully addressed occurs when the expert advice is imperfect, which can lead to poorer models. We propose a model that extends KBSVMs and is able to not only learn from data and advice, but also simultaneously improves the ad...

The aim of this paper is to expound an original algebraic model for managing the knowledge provided by different expert humans when developing expert systems. This model is conceived as an extension of classical propositional logics in which each proposition is associated with a set of human experts who agree with it. In our model, the logical notions of tautological consequence and consistency...

The paper explores the rise of activity-based costing (ABC). Drawing on actor-network theory, we follow key actors, and their intermediaries, as they construct ABC through a network of human and non-human allies. Drawing on Giddens’ discussion of the dynamics of modernity, we show how ABC is formed, and reformed, in processes of disembedding and reembedding, and how it becomes affiliated to ‘ne...

The goal of expert-finding is to retrieve a ranked list of people as a response to a user query. Some models that proved to be very successful used the idea of association discovery in a window of text rather than the whole document. So far, all these studies only considered fixed window sizes. We propose an adaptive window-size approach for expert-finding. For this work we use some of the docu...

Human genetics is undergoing an information explosion. The availability of chip-based technology facilitates the measurement of thousands of DNA sequence variation from across the human genome. The challenge is to sift through these high-dimensional datasets to identify combinations of interacting DNA sequence variations that are predictive of common diseases. The goal of this paper was to deve...

Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporat...