Machine learning and natural language processing (NLP)

Trained in some of the finest universities around the world, Winot engineers have been focusing on modern advances in artificial intelligence. In order to deliver high-quality intelligent software systems we have to assimilate a wide range of ideas and practices from computational learning theory. In practice, we design intelligence bearing in mind two important goals: learning and communication.

For the first part we use methods ranging from statistical machine learning to data mining. Modern businesses are often faced with the problem of analyzing enormous amount of data. In Winot we do not make superficial use of these technologies but rather strive to achieve the goal set by Richard Humming “The goal of computing is insight, not numbers”. Our methodology is to work closely with industry people and use their insight to employ modern machine learning tools as succinctly as possible.

For the second part, we take pride in being one of the first Hellenic organizations that have marched towards the development of complete NLP systems and their integration to our solutions. We are thus able to implement software modules that are capable of parsing a large corpus of text information written in common language (e.g. news, websites) and distil important information that are relative to business strategies.