Author : Manigandan. J 1
Date of Publication :7th March 2016
Abstract: Web mining is used to discover as well as extract data from web documents and service. Social networking sites are used to discuss the current topics and reactions to current happening on the internet. The discussion which reflects the opinion of people, thoughts and their innovative ideas. Detection of current topic and tracking valid data from offline articles is quite difficult. Detection of topic from social networking sites will helps to gather and analyses the huge volume of up-to-the minute. Topics are detected based on vigorously and provides path to various treatments to cure the diseases. The techniques are called as Formal Concept Analysis  based on Matrix Factorization are intended to pick up the evolution and issues of current topic in unstructured content which are present in a social media. Extraction and analyses of data based on the user-needed data content. Self organizing maps  are used to correlate the data based on positive and negative words present in the users status. Scores of text will give as numerical value of each user forums. The pictorial representation can be viewed based on the scored values and for easy understanding. It helps to determine the better treatments and least cost medicine to cure incurable diseases can be identified and try to cure by early stage as soon as possible.
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