Review on QA Performance Improvement using Multimedia Techniques

Abstract

CQA (Community question Answering) which is the record of millions of question and answer which is created. CQA user to provide a rich resources of information which is missing at Web Search Engine and to automate and enhanced the process of locating the high-quality answer question at a CQA.CQA archived the question that are matched by the CQA system with respect to QA which significantly minimizes the user time and efforts involved in searching for answer to Question. CQA forum usually provide only the textual answer which are not enough for many question. In this paper, we propose a scheme that will be able to enrich textual answer in CQA with appropriate using of media data. In this project our scheme consists of 3 components such as the Answer Medium Selection, The Query Generation for Multimedia, The Multimedia data Selection and Presentation. In this our approach is to automatically determine which type of the media information can be added to enrich the textual answer. In this by processing for large datasets QApair and adding them to a pool, in this our approach as a user’s can find multimedia question answer (MMQA) by matching their questions with those in the pool. Different from a lot of multimedia QA research efforts that attempt to directly answer the question with Image and Video data. In this our approach is built based on Community Contributed Textual Answer and can deal with more complex questions. In this we have also conducted extensive experiment on a multi-source QA datasets there the result Demonstrate the effectiveness of our approach
DOI: 10.17762/ijritcc2321-8169.150812