Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasing popularity of Social Media has resulted in the cre- ation of a huge amount of user generated documents. A large number of research works have focused on inferring relationship in certain spe- cific social network domains. Few have considered structured data to establish syntax based relationship. In this work,  develop a two-step syntax based and semantic based relationship mining approach. Here  generalize the concept of relationship mining for all structured as ll as unstructured unsupervised text documents from all social network domains. At first,  choose suitable features from individual document and store them in graph structure. Then  establish relationships in the graph generated to obtain Reduced node Social Graph with Relation- ships (RSGR). Our empirical study on various social media document validates the effectiveness of our approach and suggests its generality in finding relationships irrespective of the type of text documents and the social network domains.
['Tuhin Sharma', 'Durga Toshniwal']
I am writing a research paper on a idea A Generalized Relationship Mining Method for Social Media Text Data
[{"from": "human", "value": "I am writing a research paper on a idea A Generalized Relationship Mining Method for Social Media Text Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Increasing popularity of Social Media has resulted in the cre- ation of a huge amount of user generated documents. A large number of research works have focused on inferring relationship in certain spe- cific social network domains. Few have considered structured data to establish syntax based relationship. In this work,  develop a two-step syntax based and semantic based relationship mining approach. Here  generalize the concept of relationship mining for all structured as ll as unstructured unsupervised text documents from all social network domains. At first,  choose suitable features from individual document and store them in graph structure. Then  establish relationships in the graph generated to obtain Reduced node Social Graph with Relation- ships (RSGR). Our empirical study on various social media document validates the effectiveness of our approach and suggests its generality in finding relationships irrespective of the type of text documents and the social network domains."}]