Deterministic Approach for data Integration in Distributed Web Information System Using Machine Learning Techniques

Abstract

The day today digital life is incorporated with data in which the collection of data describes each individual in the exact form of their occurrence in our current digital world.  The process of handling data from one source is not in a practical condition nowadays.  Each resource handles its own form of data so that their information system dependent data is always ready for their use and moreover it’s feasible for them to provide security to their data.  The distributed web information system is collection of data with different formats which requires more effort to handle it in an efficient manner.  The art of collecting the data, ordering the data, and integrating the data in a distributed web information system is a complex process to implement.  The existing methodologies focuses on the integration of results but resulted with improper classification and duplication of information collections.  This research article proposes a machine learning approach for handling heterogeneous data in distributed web information system with proper classification of data along with its unique characteristics.  In future this research paper will be improved with the implementation of artificial intelligence based distributed web information system.