1. A method for identifying duplicate documents in a memory device, comprising: drafting a first document and creating a near unique representative string (NRS) based on the document content; searching for other documents with the same said NRS, wherein said searching for other documents with the same said NRS includes computing a measure of similarity between said first document and at least a second document, comprising: receiving a first list of rated keywords extracted from the first document and a second list of rated keywords extracted from the second document; using the first and second lists of rated keywords to determine whether the first document forms part of the second document using a first computed percentage indicating what percentage of keyword ratings, in the first list also exist in the second list; computing a second percentage indicating what percentage of keyword ratings along with a set of their neighboring keyword ratings in the first list also exist in the second list when the first computed percentage indicates that the first document is included in the second document; using the first computed percentage to specify the measure of similarity when the second computed percentage is greater than the first computed percentage; selectively assigning a duplicate group identification (DGI) to said first document at time of said first document creation before depositing said first document into the memory device, said DGI is unique if no NRS matches found, or DGI is the same as an associated duplicate document's DGI that matches the NRS; placing said DGI into a meta-data of said first document; recalling from the memory device a list of duplicates of a particular document based upon user demand by searching said meta-data and selecting documents using the same said DGI; wherein, if the first computed percentage does not indicate that the first document is included in the second document, computing a third percentage using a Jaccard distance measure; and wherein if the third computed percentage indicates that the first document is a revision of the second document, computing a fourth percentage indicating what percentage of keyword ratings along with a set of their neighboring keyword ratings in the second list also exist in the first list.
1. A method for identifying duplicate documents in a memory device, comprising: drafting a first document and creating a near unique representative string (NRS) based on the document content; searching for other documents with the same said NRS, wherein said searching for other documents with the same said NRS includes computing a measure of similarity between said first document and at least a second document, comprising: receiving a first list of rated keywords extracted from the first document and a second list of rated keywords extracted from the second document; using the first and second lists of rated keywords to determine whether the first document forms part of the second document using a first computed percentage indicating what percentage of keyword ratings, in the first list also exist in the second list; computing a second percentage indicating what percentage of keyword ratings along with a set of their neighboring keyword ratings in the first list also exist in the second list when the first computed percentage indicates that the first document is included in the second document; using the first computed percentage to specify the measure of similarity when the second computed percentage is greater than the first computed percentage; selectively assigning a duplicate group identification (DGI) to said first document at time of said first document creation before depositing said first document into the memory device, said DGI is unique if no NRS matches found, or DGI is the same as an associated duplicate document's DGI that matches the NRS; placing said DGI into a meta-data of said first document; recalling from the memory device a list of duplicates of a particular document based upon user demand by searching said meta-data and selecting documents using the same said DGI; wherein, if the first computed percentage does not indicate that the first document is included in the second document, computing a third percentage using a Jaccard distance measure; and wherein if the third computed percentage indicates that the first document is a revision of the second document, computing a fourth percentage indicating what percentage of keyword ratings along with a set of their neighboring keyword ratings in the second list also exist in the first list. 12. The method according to claim 1 , wherein said DGI is a unique identifier.