LEDS Linked Enterprise Data Services
Since the most of the world’s data is unstructured, the mining of required information from text was, is and will be essential. However, the requirements for text mining are becoming more complex, as rare languages or new domains need to be supported, social media content has often a worse grammar or mixed languages, and the amount and velocity of the data growths constantly. To compete with these requirements, the current research progress regarding Deep Learning (DL) for Natural Language Processing seems to promising. Within the LEDS project, Ontos rely on them in order to develop a DL-based MINER in order to extract required information from arbitrary texts. This service is embedded into a streaming platform that allows for 1) flexible text mining with a high throughput and 2) a disambiguation and linking against existing knowledge bases. In this industry talk, we will provide insights regarding concepts, implementations, and the proof-of-concept for news and social media aggregation.
Dr. Martin Voigt received his Diploma degree from TU Dresden, Germany, in April 2009. At the same university, he worked as researcher, project manager and Ph.D. student in the field of composite web application engineering, Semantic Web technologies and Information Visualization until February 2014. Then he joined the Ontos team in Leipzig, Germany, as senior researcher and project manager where he managed several industry and research projects. In 2015, he received his Ph.D and becomes the managing director of Ontos GmbH. His current research focus is about making end users able to understand Big Data without being a data scientist or a visualization expert. Therefore, he focuses on intelligent backend technologies (Semantic Web, machine learning, NLP, etc.) but also on usable, helpful user interfaces.
