Microproject descriptions. Human Behavior is a matter of Time! – Modeling Events Interactions through Temporal Processes Date Start: 2022-09-01 Date finish: 2022-12-31 Duration: 4 months Partners:
Microproject descriptions. Human-machine collaboration for content analysis in context of Ukrainian war Date Start: 2022-06-01 Date finish: 2023-02-27 Duration: 6 months Partners:
Microproject descriptions. Neural Mechanism in Human Brain Activity During Weight Lifting Date Start: 2021-05-03 Date finish: 2022-01-31 Duration: 8 months Partners:
Microproject descriptions. Matching the right people! Creating a functional demonstrator for online matching of people and expertise for innovation Date Start: 2022-06-01 Date finish: 2022-12-31 Duration: 6 months Results: Connecting the right people with the right expertise is essential for innovation, but finding suitable collaborators can be challenging. In this micro project, we explored a novel approach that leverages publicly available performance data (e.g., Github profiles) to automatically match people and expertise for innovation. Building on such data, we developed a recommender system that suggests potential collaborators based on their demonstrated expertise. The project builds on the previous two micro projects, which identified a set of functional questions to match people for innovation and implemented a prototype for creating user profiles based on those questions. In this third micro project, we developed a demonstrator that creates recommendations for collaboration based on the automated collection and analysis of GitHub data. In contrast to the previous micro projects, the approach focuses on demonstrated expertise, rather than relying on self-reported knowledge, which can be inaccurate or incomplete. To develop the demonstrator, we used the GitHub API to retrieve information about users' activities and built a recommender system that suggests potential collaborators based on their GitHub statistics. We also created a user interface for founders to find potential co- founders based on the expertise shown. This system offers a reliable and objective way of matching people with the right expertise, which can be especially valuable in high-tech environments where expertise is critical for success. We evaluated the effectiveness and usability of the developed recommender system and user interface through a series of interviews and online studies. First, we interviewed domain experts to establish the requirements and important features of the model. Second, we interviewed potential founders to evaluate the general approach and gather feedback on the recommender system. Finally, we conducted an online study to evaluate the usability of the user interface. The study involved a group of participants using the interface to find potential collaborators and provide feedback on their experience. Overall, the evaluations provided valuable insights and feedback for improving the system's effectiveness and usability. We plan to incorporate the feedback from the evaluations to f...
Microproject descriptions. The description of the MP “Matching the right people! Creating a functional demonstrator for online matching of people and expertise for innovation” can be found in Section 6.2.
