Productive Data integration in Web data Mining Using Contingency Approach
A Velanganni, Sandra Victor · Journal of Emerging Technologies and Innovative Research · 2020
We are living in the extended digital era in which the digital data is emphasized with heavy impact on every component in our activities. Each activity or event has its own set of data stored, accessed and manipulated in the web servers, the process of accessing the web data is slowly categorized itself into several entities. Different servers hold its own way of storing information's the users who require the flexibility in accessing the individual server is easy but the way of getting an integrated data from multiple servers are difficult due to its heterogeneous nature of different formats ,type, patterns, techniques and accessibility features. Web data integration is an important role in our modern digital era for its time and space complexity effectiveness. The process of integrating web data is a complex process due to its variety, value and velocity which extends the tediousness in productive or qualitative data integration based on user requirement is essential for effective web data accessibility and usage. This paper deals with the productive web data integration using contingency approach for effective web data integration. In near future we will implement the advanced neural network based web data integrity for optimal productive data integration in web data mining.