In his thesis, Irtaza Rasheed implementated a universal name disambiguation approach that considers almost any existing property to identify authors. After an author of a paper is identied, the normalized name writing form on the paper is used to refine the author model and even give an overview about the different writing forms of the author’s name. This can be achieved by first examine the research on Human-Computer Interaction specifically with focus on (Visual) Trend Analysis. Furthermore, a research on different name disambiguation techniques. After that, building a concept and implementing a generalized method to identify author name and affiliation disambiguation while evaluating different properties.
In his thesis, Midhad Blazevic alyzes exploratory search systems which use sophisticated features, visualizations and similarity-based algorithms to enhance exploratory searches. Examining how similarity algorithms are currently used in combination with elements from information retrieval, natural language processing and visualizations, but also examine what exploratory search is, what the requirements are and what makes it so special in modern times. Furthermore, the user himself or herself will be analyzed as user behavior during exploratory searches is a key factor that has to be taken into consideration when looking to optimize the exploratory search process overall. Based on these aspects, means of improvement will be developed and showcased, which will be used to determine if there is an improvement in comparison to other well-known systems. The outcome of this thesis will present a prototype of an exploratory search system along with a practical use case.
IEEE is the world’s largest professional association dedicated to advancing technological innovation and excellence for the benefit of humanity. IEEE has more than 423,000 members in more than 160 countries working to inspire a global community through publications, conferences, technology standards, and professional and educational activities.
Prof. Dr. Kawa Nazemi has been elevated to senior member of IEEE. The IEEE Board of Directors announced this decision in a virtual meeting in June 2020.
The IEEE Senior Membership is only awarded to a very limited number of members who have contributed significantly to the further development or application of science and technology. Less than 8% of the members worldwide are awarded senior member status based on their merits in research, profession and teaching.
Mina Schütz wrote her master thesis under the supervision of Prof. Dr. Kawa Nazemi and Prof. Dr. Melanie Siegel toward “Detection and Identification of Fake News: Binary Content Classification with a Pre-Trained Language Model” at Austrian Institute of Technology (AIT), Center for Digital Safety & Security in Vienna. During her work, she could successfully conceptualize and develop a system that enables the classification of news with a high probability as fake or real on the basis of Artificial Intelligence algorithm. The work is a great product of scientific and empirical acting and will be published in the scientific world soon.
For her excellent work and the high societal relevance, the impact magazine of the h_da has interviewed her to outline the topic and her approach in a better understandable manner, particularly for non-computer-science experts. The full interview is available (in German only) on: https://impact.h-da.de/forschung/corona-und-fakenews/.
At the next conference in Virtual and Augmented Reality in Education (VARE 2019), we are happy that out paper toward mobile visual trend analytics was accepted for presentation. The conference takes place from Sep. 18 to Sep. 20, 2019 in Kisbon, Portugal. The VARE is an annual event that brings together trainers in all areas of knowledge and educational levels as well as researchers and scientists from virtual technologies as well data advanced visualization and virtualization. In general, main aim is to improve teaching and training, and data analysis through virtual and augmented technologies use and to discuss problems and solutions in mentioned areas to identify new issues, and to shape future directions for research.
Paper: A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts
The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.
Link to paper/fulltext: -comming soon-