8. A system for rectifying a typographical error in a text file, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of module comprising: a network generating module configured to generate a linguistic network of a plurality of words present in the text file, wherein each pair of words of the plurality of words in the linguistic network is interconnected via an edge; a computation module coupled to the network generating module, the computation module configured to compute similarity between the each pair of words based on a set of parameters associated with words of each pair, wherein the set of parameters comprises distance between the words, phonetic similarity between the words, consonant skeleton distance, presence of the words in lexicon, morphological root form of the words, frequency of the words in the text file, probability of occurrence of the words in the context, domain similarity of the words, and a flag associated to similar starting character of the words; a weight assignment module configured to assign a weight to the edge between the each pair of words based on the similarity computed from the set of parameters; a categorization module configured to categorize one or more words present in the linguistic network in a category, wherein the one or more words are categorized based on the weight assigned to each edge connecting the each pair of words of the one or more words; a word identification module configured to identify a reference word for each word which is deemed to have the typographical error from the category; and a word substitution module configured to substitute each word of the category, having the typographical error, with the corresponding reference word in the text file for rectifying the typographical error.
8. A system for rectifying a typographical error in a text file, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of module comprising: a network generating module configured to generate a linguistic network of a plurality of words present in the text file, wherein each pair of words of the plurality of words in the linguistic network is interconnected via an edge; a computation module coupled to the network generating module, the computation module configured to compute similarity between the each pair of words based on a set of parameters associated with words of each pair, wherein the set of parameters comprises distance between the words, phonetic similarity between the words, consonant skeleton distance, presence of the words in lexicon, morphological root form of the words, frequency of the words in the text file, probability of occurrence of the words in the context, domain similarity of the words, and a flag associated to similar starting character of the words; a weight assignment module configured to assign a weight to the edge between the each pair of words based on the similarity computed from the set of parameters; a categorization module configured to categorize one or more words present in the linguistic network in a category, wherein the one or more words are categorized based on the weight assigned to each edge connecting the each pair of words of the one or more words; a word identification module configured to identify a reference word for each word which is deemed to have the typographical error from the category; and a word substitution module configured to substitute each word of the category, having the typographical error, with the corresponding reference word in the text file for rectifying the typographical error. 11. The system of claim 8 , wherein the word identification module is further configured to: compare each word of the category with a lexicon vocabulary to verify at least one word of the category is present in the lexicon vocabulary, wherein the at least one word is assigned a flag, and wherein the flag associated to the at least one word is indicated as the reference word; or select the reference word from the lexicon database by computing the at least one of the distance and the phonetic similarity between each word of the category and the lexicon vocabulary, wherein the reference word is selected when the at least one word of the category is not present in the lexicon database; or determine a number of instances associated to each word of the category in the text file, wherein the number of instances is determined to select the reference word having highest number of instances in the text file and wherein the number of instances is determined when the reference word is not selected based on the computing.