2017-10-27 | Towards utilization of grammatical information in question answering (Jyrki Nummenmaa)
Text analysis is a fundamental task with many applications such as information retrieval, analysis of recommendations, question answering, and various task related with AI. The bag-of-words and k-gram based methods have, as initial basic approaches, have been followed by the use of machine learning techniques such as deep learning. However, grammar is what creates conceptual content out of words. Therefore, we suggest a grammatical analysis of text as a basis for analyzing texts. We present an example case where we apply the grammatical approach in a particular question answering task. We get results comparable to the use of neural networks, however the results are also explainable.
Mr. Jyrki Nummenmaa is a full professor at the School of Information Sciences of University of Tampere, Finland and the head of Research Center for Information and Systems (CIS) at the University of Tampere.
Prof. Nummenmaa has done research on algorithms, databases, software development, business intelligence, data mining, open data, and Big Data, and, most recently, in text analysis. He has extensive administrational experience and he has practical experience of working 3,5 years in software companies in Tampere area. He has visited the University of Edinburgh for one year while doing his PhD research and lately several times universities in China, in 2004 University of Chile for 2 months, and in 2017 IT Faculty of Chalmers and University of Gothenburg for 2 months. He has over 70 peer-reviewed scientific publications in scientific journals and conferences.