2. The method according to claim 1 , further comprising: applying parts-of-speech tags to the text documents and user question to generate tagged text documents and user question; parsing the tagged text documents and user question to generate parsed and tagged text documents and user question; and semantically analyzing the parsed and tagged text documents and user question to generate semantically analyzed, parsed, and tagged text documents and user question.
2. The method according to claim 1 , further comprising: applying parts-of-speech tags to the text documents and user question to generate tagged text documents and user question; parsing the tagged text documents and user question to generate parsed and tagged text documents and user question; and semantically analyzing the parsed and tagged text documents and user question to generate semantically analyzed, parsed, and tagged text documents and user question. 11. The method according to claim 2 , wherein identifying one or more target words in the user question using linguistic patterns stored in the database and assigning a question type to each of the one or more target words in the user question comprises matching the semantically analyzed parsed, and tagged user question against question classification based linguistic patterns in a patterns database that is a part of a linguistic knowledge base using, at least in part, the following steps: determining part of-speech tags, syntactic tags, and semantic labels of words in the user question and determining eSAO sets and cause-effect sets from the words of the user question; generating eSAO labels and cause-effect labels from the eSAO sets and cause-effect sets; and matching the eSAO labels and cause-effect labels to semantic labels of question types for target words.