1. A computer-implemented, informational retrieval system for real-time, interactive semantic curation from a networked database, the system comprising: (a) a gloss vector engine configured with means to generate semantic gloss vectors for data mining by unsupervised machine learning; (b) a deconstruction engine configured with means to identify well-formed sentences; (c) a data discovery engine configured with means to identify indirect communicating links; (d) a collocation engine configured with means to identify compound nouns; (e) a disambiguation engine configured with means to assign nouns that fit the context of the sentence in which said nouns occur; (f) a generic noun disambiguation engine configured with means to identify context shifts produced by use of nouns selected from the group of generic nouns, common nouns; (g) a pronoun disambiguation engine configured with means to link common nouns to proper corresponding nouns; (h) a data evaluation engine configured with means to identify well-formed sentences containing information of maximal semantic value; (i) a retrieval engine configured with means to return information with maximal semantic value score for a given search term; (j) a context targeting engine configured with means to display in context the specific output sentence that is generated by the input query, in the context of the source article containing said sentence; wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus.
1. A computer-implemented, informational retrieval system for real-time, interactive semantic curation from a networked database, the system comprising: (a) a gloss vector engine configured with means to generate semantic gloss vectors for data mining by unsupervised machine learning; (b) a deconstruction engine configured with means to identify well-formed sentences; (c) a data discovery engine configured with means to identify indirect communicating links; (d) a collocation engine configured with means to identify compound nouns; (e) a disambiguation engine configured with means to assign nouns that fit the context of the sentence in which said nouns occur; (f) a generic noun disambiguation engine configured with means to identify context shifts produced by use of nouns selected from the group of generic nouns, common nouns; (g) a pronoun disambiguation engine configured with means to link common nouns to proper corresponding nouns; (h) a data evaluation engine configured with means to identify well-formed sentences containing information of maximal semantic value; (i) a retrieval engine configured with means to return information with maximal semantic value score for a given search term; (j) a context targeting engine configured with means to display in context the specific output sentence that is generated by the input query, in the context of the source article containing said sentence; wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. 4. The data discovery engine in the computer-implemented, information retrieval system of claim 1 , further comprising an Acronym and Abbreviation Identifier Module, a Compound Noun Identifier Module, a Definition Discovery Module and a Text/Title Relationship Identifier all with means to establish indirectly communicated information selected from the group comprising compound words, abbreviations, acronyms, definitions, and relationships between text and title.