An Efficient Way of Answering the Questions Asked on Social Sites by Understanding User Intent

摘要

Information seeking is human nature. Nowadays sharing knowledge and facts on social network has become very important aspect. Communication is required for solving queries and getting answers. Social sites provide such platform where people can post their queries and get various point of views. Relative comparison of the search engines such as Google, Bing, and Social Q-A sites, later provides more explicit and user-friendly interface for expressing information needs as users can publically post their questions in natural language to all their friends or followers online and receives more personalized and reliable responses. This is useful only if the intent of the interrogator is correctly predicted. Understanding the user behind posting the question plays important role in answering that question. The accuracy of the answer can be improved by correct prediction of the user intent. So, the proposed work includes identifying the question subjectivity of any question posted on social sites. On the basis of various syntactical and lexical features, question subjectivity can be divided into two parts namely subjective and objective. Depending on the result of question classification, the answer of the question will be provided. The database consists of several types of questions posted on social media and not confined to the particular social site. The proposed work defines an efficient way to answer the question depending on the result of question classification.