NLP combines the techniques of statistics with machine learning. This makes it possible to extract keywords from a text. We can then use this to make important classifications. TNO uses NLP to extract information from extensive, unstructured textual data in a more automated way.

Text mining

Text mining refers to the process of analysing and processing textual data to derive higher-quality information from these texts.

Word embeddings

Word embedding is a technology in Natural Language Processing (NLP). The aim is to have a representation of text into a vector space, where semantically similar texts are close to each other. There are two approaches: representing words as vector of co-occurring words and as vectors of context words. Various techniques have been used, though currently mostly neural network based techniques.

What does TNO offer on Natural Language Processing?

At TNO, we use our tools to automatically extract information from documents. We can also make predictions, such as in the foresight domain. Using the Horizon Scanner, we explore and extract from relevant websites, blogs and documents. This allows us to retrieve relevant information and to show trends. Trend analysis shows us that the term deep learning is now being mentioned much more frequently within the computer vision domain than it was ten years ago. In addition, we can classify the documents automatically. For example, by a particular topic or field. We can also use blogs to conduct sentiment analysis and find out whether terms are being described more positively or negatively.