1. A method for unsupervised learning of a grammatical parser and the use thereof, wherein the method comprises: providing a processor on a computer, wherein the processor runs a content acquisition system to obtain a corpus of text documents over a computer network; storing the corpus of text documents from the content acquisition system on a storage device; providing a processor on the computer which runs a text analytics engine, wherein the text analytics engine comprise a core algorithm, and a factorization algorithm; using the core algorithm to: divide the corpus of text documents into a plurality of sentences; divide the sentences from the plurality of sentences into a plurality of text units; join the text units from the plurality of text units into a plurality of grammatical links; and using the factorization algorithm to factorize a matrix or a tensor for each of the grammatical links of the plurality of grammatical links to respectively generate a plurality of factorized matrices or a plurality of factorized tensors; and additionally using the core algorithm to: generate parses from a corpus of a novel document, comprising: divide the corpus from the novel document into a plurality of sentences; divide the sentences from the plurality of sentences from the novel document into a plurality of text units; identify a subset of all possible grammatical links from the plurality of text units from the novel document; and determine the relative likelihood of the grammatical links in the corpus of the novel document by using the factorized matrices or the factorized tensors to compute a score representing the likelihood of the grammatical links.