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Authors
Affiliations
1 Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, Erode-638052, Tamilnadu, IN
Source
International Journal of Scientific Engineering and Technology, Vol 2, No 10 (2013), Pagination: 943-946
Abstract
As information has been increasing enormously in the world, it is very difficult to retrieve information as per the user satisfaction. The main objective of this project is to retrieve the information that is more relevant to user query. The optimization technique used here is Genetic Algorithm (GA). A genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms, which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
In this work the Document Crawler is used for gathering and extracting information from the documents available from online databases and other databases. Since search space is too large, Genetic Algorithm (GA) is used to find out the combination terms. In the proposed document retrieval system, need to extract the keywords from the document crawler and with these keywords GA generate combination terms. To obtain better combination terms, need to calculate the fitness function based on the frequencies of keyword. The keyword frequency can be generated by counting occurrences of word in a document.
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