This paper is based on the pulling out of key terms that have the aptitude to describe the meaning of a manuscript. The initial step of text mining process like clustering, classification, summarization etc involves the phase of term or keyword identification that helps describe the topic of the document. In this paper the use of genetic engineering in the above mentioned phase has been demonstrated. Researches performed prove that the genetic algorithm serves as an optimization technique for the generation of the topic terminologies of the passage or document. It is seen that two terms can possess the same frequency in a single document but one term contributes more to the meaning of the corpus. Thus it is necessary to take into consideration various features like word position, maximum number of words in a sentence, total number of words in a document, etc to extract the terms. Considering all these features, this paper shows a clear view of a new genetic algorithm using an enhanced derivation method for extracting keywords from the text document.

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