Comprehensive Approach for data Integration in Legacy System based Distributed Web Information Domain Using Machine Learning Techniques
Keywords:
Legacy system, Machine learning, web data, distributed data, heterogeneous dataAbstract
Legacy systems in data integration are the outdated hardware or software systems acts as the hurdle towards the effective data integration operation. The legacy systems stored their data bases information which are not feasible to link with the recent distributed data information integrated system due to its ineffectiveness and compatibility issues. The new technologies and open standards are not easily coping up with the existing legacy systems if it is not handled with proper care. Most of the past data integration schema dealt with these legacy systems which are common in use but they will act as an essential component in the future references. The existing methodologies target towards the integration of legacy data without care about its infrastructure and data classification resulted in failed integrated information collections. This research article proposes a machine learning approach to deal with the legacy systems in distributed web information domain with proper machine learning approach with its unique characteristics. In future this research paper will be extended with the implementation of genetic algortihm based distributed web information system.
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