Investigation of Genetic Algorithm on XML Data Based Content Search

Dipali Tungar, Prof. Amol D. Potgantwar

Abstract


In a traditional keyword-search system over XML data, a user creates a query, submits it to the system to get the answers. While querying, user must has knowledge about the data otherwise appropriate result will not be retrieved. If the user does not have knowledge about the underlying complex database schema then user feels helpless while querying and get tired by wait and watch approach. In another approach user inputs the search query in terms of keyword or a question. Keywords are suitable for query XML streams without knowing the schema information. Sometime the traditional algorithms, which are used for XML data search using keyword search may lead to irrelevant results.

Genetic algorithms are the modern algorithms, which replicates the Darwinian theory of the natural evolution. The genetic algorithms are best suited for the traditional search problem, as the genetic algorithms always tend to return quality solution for any domain data. This would be a good approach to investigate how the genetic algorithms would be suitable for the search over the XML data. Therefore, this system implements a steady state tournament selection Microbial Genetic Algorithm over the XML data of the different domains.

This system has the following features: 1) It can find high-quality answers that have keywords matching query keywords.2) Genetic Algorithm can achieve a very high interactive speed. We have implemented our method on real data sets, and the experimental results show that our method achieves high search efficiency and result quality.


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