Using Conventional MMQA To Automatically Annotate Media Entities
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 11
Abstract
It is worth stating that already exist several research efforts enthusiastic to automatically answering questions with multimedia data i.e. the so-called Multimedia Question Answering (MMQA). But these approaches generally work on definite narrow domains and can barely be generalized to handle questions in broad domains. This is due to the fact that in order to complete automatic MMQA we first need to understand questions which are not an easy assignment. Our proposed approach in this work does not aim to directly answer the questions and instead we augment the community-contributed answers with multimedia contents. The plan divides the huge gap between question and multimedia answer into two smaller gaps i.e., the gap between question and textual answer and the gap between textual answer and multimedia answer. In our scheme the first gap is linked by the crowd-sourcing intelligence of community members and thus we can focus on solving the second gap. Therefore our scheme can also be viewed as an approach that achieved the MMQA problem by jointly exploring human and computer. The proposal of a novel scheme which will enrich community-contributed textual answers in cQA with appropriate media data.
Authors and Affiliations
Kondapalli. V V SubbaRao, V. Chandra Kumar
Keywords
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