The WDAqua ITN: Answering Questions using Web Data
Christoph Lange, Saeedeh Shekarpour, Soren Auer

TL;DR
The WDAqua ITN project focuses on advancing data-driven question answering by integrating training, research, and innovation, with practical applications across various sectors and fostering transferable skills for researchers.
Contribution
It introduces a comprehensive training and research program that connects multiple steps of question answering, promoting interdisciplinary and transferable skills.
Findings
Development of question answering techniques for diverse applications
Training program enhances researcher skills and industry readiness
Research results applicable to e-commerce, public sector, and smart cities
Abstract
WDAqua is a Marie Curie Innovative Training Network (ITN) and is funded under EU grant number 642795 and runs from January 2015 to December 2018. WDAqua aims at advancing the state of the art by intertwining training, research and innovation efforts, centered around one service: data-driven question answering. Question answering is immediately useful to a wide audience of end users, and we will demonstrate this in settings including e-commerce, public sector information, publishing and smart cities. Question answering also covers web science and data science broadly, leading to transferrable research results and to transferrable skills of the researchers who have finished our training programme. To ensure that our research improves question answering overall, every individual research project connects at least two of these steps. Intersectional secondments (within a consortium covering…
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Taxonomy
TopicsExpert finding and Q&A systems · Mobile Crowdsensing and Crowdsourcing
