Читать книгу Cognitive Engineering for Next Generation Computing - Группа авторов - Страница 30

In the diagram data access level has portrayed the principle interface connecting the cognitive system and the external world. Any information that is needed has to be imported from outer sources has to go through the procedures inside this layer. All types of structured, semi-structured, and unstructured data are required for the cognitive application is collected from different resources, and this information is arranged for processing using the machine learning algorithms. To put an analogy to the human way of learning is that it represents the senses. There are two tasks that the feature extraction layer needs to complete. One is identifying the significant information and the second is to extract the information so that it can be processed by the machine learning algorithms. Consider for instance with image processing application where the image representation is in pixels and it does not completely represent an object in the image. We need to represent the things in a meaningful manner as in the case of the medical images, where a dog or dog scan is not useful to the veterinary doctor until the essential structure is captured, identified, and represented. Using Natural Language Processing the meaning in the unstructured text can be identified. The corpus is dynamic hence the data is added or removed from it constantly by using the hypotheses score.