Patent Document ID: 8583419
Application ID: 12450575

Base Claim:
1. A computer-implemented method for advance and/or unsupervised machine learning by Latent Metonymical Analysis and Indexing (LMai), said method comprising steps of: a. inputting natural documents; b. eliminating special characters to count a number of words within the given document, filtering the contents of the document based on a list of predefined stop-words and calculating a fraction of the stop-words present in the document; c. determining a Significant Single Value Term data set and a Significant Multi Value Term data set from the document; d. decomposing words in the Significant Single Value Term data set and the Significant Multi Value Term data set to extract Keywords of the document being processed; e. optionally, determining KeyTerms and their respective hand-in-hand (HiH) words automatically for further decomposition, wherein the hand-in-hand (HiH) words are words that go together as one word; f. identifying a Topic in an unsupervised manner based not just on a File Name but also by manipulating/comparing with various combinations of document attributes that are extracted to select Best Topic candidates and thereafter defining an appropriate Topic based on predefined rules using a computer; and g. analyzing relationship between the identified Topics and the Keywords and thereafter indexing the Topics and their related Keywords, KeyTerms and their respective hand-in-hand terms into a Metonymy cluster and a KeyTerms HiH cluster respectively.

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Claim 2:
2. The computer-implemented method as claimed in claim 1 , wherein the method uses a self-learning process to make decision in identifying the relationship between the words in natural documents in any electronic file format converted into a tokenized format before data is given to the method to perform the classification of relationship between the related words without any human guidance by virtue of defining an appropriate Topic for a given document based on its content.