Extraggo provides a seamless combination of statistical and semantic techniques. Statistical machine learning is applied to identify the key terms in the input text, whereas semantic text understanding, provided by Comprehendo, enables linking terms to concepts and entities as available in the WordAtlas knowledge graph. Terms, concepts and entities are ranked by importance, and the domain and sentiment information conveyed in the text are provided. Thanks to its tight interaction with Comprehendo and WordAtlas, Extraggo makes it possible to distill knowledge from text written in multiple languages, including non-standard text, such as bags of words or search queries.
Features
Statistical Extraction of Terms: Extraction and ranking of key terms mentioned in the text
Semantic Extraction of Concepts and Entities: Generalization of terms to concepts and named entities (e.g., different mentions to the same entity are grouped into a single item)
Language Independence: Concepts and entities are linked to WordAtlas, which enables language independence
Domain Indentification: Identification of the domains (i.e., fields of knowledge) of the text
Comprehensive Sentiment Analysis: Sentiment analysis performed at all levels: whole text, paragraphs, sentences and individual terms, concepts and entities
