An Efficient Map Reduce-Based System to find Userlikeness on Social Networks
Day to day Social network information growth pursues an exponential pattern, and Present DB management systems cannot manage efficiently such a huge volume of data. It is essential to employ a “big data” solution for Social network problems. One of the most important problems in Social network is finding User likeness (ULi). Current methods for finding ULi are not flexible and do not sustain all data sources, nor can them accomplish user necessities for a query tool. In this paper, we propose a reliable and data available method to solve ULi problems over MapReduce design. RiDaULi supports storage and retrieval of all kinds of data sources in an appropriate manner. The dynamic nature of the proposed method helps users to define conditions on all entered fields. Our assessment shows that we can use this method as high confidence in less execution time.
