15. A computer implemented method for identifying word-senses, the method comprising: generating, using a computer, a set of domain tables each comprising one or more arrays of aggregated statistical information corresponding to a plurality of words, one or more word-senses corresponding to the plurality of words, and temporal properties corresponding to the plurality of words, wherein the aggregated statistical information of words comprises temporal frequency of occurrence of words, wherein the temporal frequency of occurrence of words comprises a frequency of usage of words and corresponding word-senses during a specific time period; receiving a word; identifying, using the computer, the temporal frequency of occurrence corresponding to the received word from each domain table in the set of domain tables; associating, using the computer, the received word with a domain table in the set of domain tables, based on the temporal frequency of occurrence of the received word corresponding to the received word in the domain table meeting a threshold value; and identifying, using the computer, one or more word-senses corresponding to the received word based on one or more corresponding word-senses in the associated domain table based on the specific time period and one or more corresponding word-senses in a corresponding domain dictionary.
19. The method of claim 15 , further comprising: identifying at least two word-senses corresponding to the received word; assigning corresponding confidence values to the at least two word-senses, wherein the corresponding confidence values are based on the frequency of occurrence of the received word within one or more domain tables in the set of domain tables associated with the received word; and ranking the one or more word-senses based on their corresponding confidence value.