Understanding language has been at the forefront of artificial intelligence research and development for over a decade. Historically, natural language processing has been very challenging for computers. Developers have attempted to use statistical-based approaches that look at the probabilistic characteristics of words within a sentence. However, these methods have very poor accuracy. Other methods have involved creating a set of rules that are then used to categorize and understand a sentence. Unfortunately, the complex nature of the human language does not allow for it to be segmented according to a set of predefined rules.
Humans are naturally very good at understanding linguistic patterns and identifying influencing portions of sentences. For instance, it is very easy for humans to understand the significance of a sentence, such as the difference between “I had a bomb pizza at a restaurant in New York” versus “I am going to bomb the pizza restaurant in New York.” Both of these sentences have vastly different semantics but have only subtle structural differences.
Recently, deep learning based solutions have been shown to out perform all other algorithms with regard to natural language processing. By assuming no prior knowledge of language, deep learning algorithms are able to create their own understanding of language and automatically design a set of features that accurately describe a wide range of language problems.
Soteria Intelligence has pioneered many deep learning based natural language processing algorithms. Our artificial intelligence team has developed a wide range of custom natural language processing solutions, and we have helped companies understand, manage and monitor vast amounts of social media language content.