1. A computer implemented method for automatically determining an impact of a document on a topic of interest, without any programming, using linguistic analysis, wherein the same text can have different impact for different topics of interest, without using statistical methods and frequency or word pattern based methods, the method comprising instructions carried out by a processor of the computer for: generating at least one cluster of document text from a plurality of semantically related textual clauses across multiple sentences of text of a single document through co-referencing without statistical methods or frequency or word pattern based methods, or any manual review, by applying semantic relationship strength rules based on the type of co-referential relationship in the text; identifying at least one representative concept from the document text from a plurality of concepts of the at least one cluster of semantically related sentences from the same document, using priority scores assigned using configurable linguistic rules; wherein the representative concept can be from any sentence in the cluster; wherein other non-representative concepts are not considered for further analysis and where the same representative concept may not be representative in another document; determining at least one category for the document based only on one or more representative concepts of the one or more cluster of semantically related sentences, using configurable classification rules; computing an impact of a first clause of text of the at least one cluster of semantically related text sentences from the same document with respect to the at least one category using at least one configurable linguistic impact analysis rule using part of speech roles of words in the clause without statistical methods or frequency of words or patterns, or use of other documents and where the impact is not the same for every instance of the clause across different documents or for the same clause for every category; calculating an impact of the at least one cluster on the at least one category by aggregating the impact of all clauses of all semantically related sentences in the cluster in the same document in accordance with at least one configurable impact analysis rule using part of speech roles of words in the clause text, without statistical methods or frequency of words or patterns; wherein the impact of various clauses can negate or amplify the overall impact; wherein the impact is not the same for every instance of the clause across different documents or for the same clause for every category; and calculating the impact of the document on the at least one category by aggregating the impact of all clusters of semantically related sentences in the same document in accordance with at least one configurable document level impact analysis rule pertaining to how the impact of various clusters are to be combined.
12. The method of claim 1 , further comprising: automatically generating clusters of semantically related clauses from different sentences in the same document using co-referential relationship scores; wherein the co-referential score is determined by a scoring algorithm based on the type of co-reference without statistical methods or frequency or word patterns.