  Blogs and social networking sites serve as a platform to the users for
expressing their interests, ideas and thoughts. Targeted marketing uses the
recommendation systems for suggesting their services and products to the users
or clients. So the method used by target marketing is extraction of keywords
and main topics from the user generated texts. Most of conventional methods
involve identifying the personal interests just on the basis of surveys and
rating systems. But the proposed research differs in manner that it aim at
using the user generated text as a source medium for identifying and analyzing
the personal interest as a knowledge base area of users. Semantic graph based
approach is proposed research work that identifies the references of clients
and users by analyzing their own texts such as tweets. The keywords need to be
extracted from the text generated by the user on the social networking sites.
This can be made possible by using several algorithms that extracts the
keywords automatically from the available content provided by the user. Based
on frequency and degree it ranks the extracted keywords. Furthermore, semantic
graph based model assists in providing useful suggestions just by extracting
the interests of users by analyzing their contents from social media. In this
approach graph comprises of nodes and edges where nodes represents the keywords
extracted by the algorithm and edges shows the semantic connection between the
nodes. The method does not require internet related user activities like
surveys or ratings to gather user interest related information.
