Abstract

Micro-blogging is a popular technology in social networking applications that lets users publish online short text messages (e.g., less than 200 characters) in real time via the web and SMS. Micro-blogging is a informal communication medium especially for collaborative work within an organization. It is a novel application of text categorization for two types of micro-blogging questions asked in a classroom, namely relevant (i.e., questions that the teacher wants to address in the class) and irrelevant questions. Prior work on teacher agents includes a question ranking capability that scores each question and tries to select the best questions to respond to. The relevant question would be given the first priority for the reply, as compared to irrelevant question. They utilize the question text as well as a personalized approach (i.e., questions from a student who has been asking good questions are favored) to differentiate between the relevant and irrelevant questions. Furthermore, empirical results also show that the elimination of stop words leads to better correlation estimation between questions and leads to better categorization efficiency. On the other hand, incorporating students’ votes on the questions does not improve categorization efficiency, to be effective in community question answering environments for assessing question quality.

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