Abstract: A smart document generator receives a natural language text that comprises a plurality of text regions, performs natural language processing analysis of the natural language text to determine one or more semantic relationships within the plurality of text regions, generates a search query based on the results of the natural language processing to search for additional content related to at least one text region of the plurality of text regions, and transmits the search query to available information resources. Upon receiving additional content items that each relate to a respective text region in response to the search query, a combined document is generated that includes a plurality of portions, each of the plurality of portions comprising one of the plurality of text regions, and at least one of the plurality of portions further comprising one or more of the plurality of additional content items that relate to a respective text region.

Abstract: A method and system for text data analysis by performing deep syntactic and semantic analysis of text data and extracting entities and facts from the text data based on the results of deep syntactic and semantic analysis, including extraction of sentiments using a sentiment lexicon constructed upon a semantic hierarchy. The data analysis can include determining sign of the extracted sentiment, aggregate function of the text data, analyzing social mood, and classifying the text data.