OBJECTIVE- DATA ANALYTICS
Information Retrieval & Data Market Technologies
The competence Data Analytics is based on the methods of information retriever, machine learning and artificial intelligence. Innovative solutions for maximum data collection are developed with and for companies or public clients. These solutions are implemented as prototypes and enable an efficient exchange between research and industry. Through this cooperation we are able to transfer Big Data Analysis solutions to industry, which can also be introduced into business processes or information technology systems. DSC also deals with Technology Enhanced Learning such as Micro- or Mobile Learning.
Our methodical procedures are not only used for data analysis, but also support data management and the integration of large data sets. Data Interaction can help with visualization and graphical illustrations. Currently, the DSC-Studio is putting together a new team that focuses on statistical data analysis. Our target groups are mainly organizations and companies that want to have a deeper insight into their data structures and data flows.
Implementation and exploitation of big data analysis and data management
Data Science actively researches the further development of current data structures and data streams. In addition, new achievements in the field of machine learning and what is happening on national and international data markets, such as Data Market Austria.
The main fields of application are currently
Data Management: data cleaning, pre-processing, validation and curation
Data Integration: structured and unstructured data, multimodal data, data selection
Data Analytics: information retrieval, data mining, sematic analysis, natural language processing, machine learning, modelling
APPLICATION AREAS FROM OUR STUDIOS
Automatic Question Generation
Dieser Prototyp extrahiert Schlüsselphrasen aus einem Textabschnitt und erstellt automatisch Fragen mit diesen Phrasen als Antwort. Dadurch kann der Aufwand bei der Erstellung von Microlearning-Inhalten deutlich verringert werden.
Semantic enrichment through definition download
This prototype enhances existing learning materials (scripts, presentations, etc.) for better answers of the chat offer for dialogue-based learning.
Knowledge transfer for Clinical Psychology
This Prototype allows comparison between existing flashcard types (e.g. multiple choice) and the new special card type and also Enables specific knowledge representation adapted to the respective knowledge domain.
Transdisciplinary Competence Teams
This prototype allows comparison between existing flashcard types (e.g. multiple choice) and the new special type of card. Enables specific knowledge representation adapted to the respective knowledge domain.
Knowledgecards for Research Organizations
Allows comparison between existing flashcard types (e.g. multiple choice) and the new special card type.
Learningcards for the Creative Industry
Allows comparison between existing learning card types (e.g. multiple choice) and the new special card type.
Document Structure Extraction
Prototype Details Prototype: Document Structure Extraction Research: [...]
Dialog Based Search
Prototype Details Prototype: Dialog Based Search Researcher: [...]
Community Detection
Prototype Details Prototype: Community Detection Researcher: Bernhard [...]
Social Microlearning FLOW
Implemented as a microservice, this prototype enables implementation into existing systems through learning platform independent interfaces.