Text Document Retrieval NLP Project with PSO Algorithm

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With the drastic increase of the digital text data on the servers, it is necessary to develop new algorithms by the researchers. Considering this fact work has focus on one of the issue of the keyword identification which is build by the different documents. Here many researchers has already done lot of work but that is focus only on the content classification. But in this work not only keywords but documents are also identified then classify. In some of previous work document classification is occur on the basis of the Prior information about the content provider. This limitation is successfully overcome in this work by classifying whole set of disputant without any background information. In this paper a genetic algorithm is proposed that classify the text document in efficient manner. Here particle swarm optimization learning algorithm is utilize for the classification which is a genetic approach. Proposed classification approach classifies the data on the basis of terms features. After perfect classification of document retrieval of document as per text query is done. Results shows that using an correct iteration with fix number of chromosomes classification of keywords and documents was done in proposed algorithm.

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