Vectors, ontologies, embeddings and sentiment analysis: how relationships between words are the foundation of NLP
Human language follows unexpected patterns. Varied forms of syntax and metaphor, together with context and repetition, make classification challenging for both humans and machines. Manual classification of unstructured linguistic data by human curators can be valuable, but without technological assistance, is time consuming and potentially rife with errors. When such “natural language” data is left untouched it is less usable. Enterprises are faced with the challenge of transforming huge amounts of this raw data into actionable intelligence.