Framework For Information Analysis of the Scientific Literature using Machine Learning

One of the dynamically up growingversatile research field is Visual analytics which can beproductively used in the area of Visual Information System Management. The visual cortex is the mostelevated data transfer capacity data channel into thehuman mind and people are known to better hold dataintroduced outwardly. The papers and the scientific documents which are submitted and published todaycontain a huge amount of alpha-numeric data. Information Collectionand Information Management system play an important role inany kind of scientific visual data system. It is a crucialprecondition to search and find data on theproductivity of the process. For a decade and more, ScientificScholarly papers and documents are published very frequently. So, it is necessary to develop a frameworkto search and find the paper to identify according to the sub domain and user request. This paper offerings main tasksexisting in Visual Information Analysis area(the combination of text-mining and image processing)and offers the best suitable novel solutions to thesechallenges.