研究室紹介

Natural Language Processing

Department of Informatics, Faculty of Information Science and Electrical Engineering

Department of Informatics, Graduate School of Information Science and Electrical Engineering

Department of Electrical Engineering and Computer Science, School of Engineering

Natural Language Processing (NLP) is a field on technology to process sentences written in natural language such as Japanese and English using computer. As informationization advances and a large amount of information is flooded, NLP focuses attention as a technology for efficiently accessing necessary / important information and for analyzing a large amount of text. With the advent of Deep Learning, the performance of various NLP technologies including machine translation has been remarkably improved, and expectations for NLP are increasing more and more. We are conducting research on identifying and clustering sentences or documents based on parameter estimation of statistical language model, and research on estimating similarity between sentences or documents by Deep Learning.
We are also conducting research on the analysis of olfactory information using a model similar to the statistical language model used in the above research. Based on the images of the activation patterns of the neurons on the olfactory bulb (the first brain part receiving the odor information) of the rats when smelling various substances and the physical and chemical properties of the substances, we are working to identify the primitives of odors and the parts of the olfactory bulb that ignites when they are detected. In addition, we are working to separate and visualize odor traces (odor source) based on measured data by multi-channel odor sensor.

Natural Language Processing

Staff

Prof. Yoichi Tomiura

The Main Research Topics

  • Research on advanced search support of academic papers
  • Study on semi-automation of content analysis on values of people understood from text
  • Clustering of the olfactory bulb area and identification of primitive odors
  • Study on separating and visualizating odor traces from measured data of multichannel odor sensor
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