Abstract

Question Answering (QA) systems are becoming the inspiring model for the future of search engines. While, recently, datasets underlying QA systems have been promoted from unstructured datasets to structured datasets with semantically highly enriched metadata, question answering systems are still facing serious challenges and are therefore not meeting users' expectations. This paper provides an exhaustive insight of challenges known so far for building QA systems, with a special focus on employing structured data (i.e. knowledge graphs).It thus helps researchers to easily spot gaps to fill with their future research agendas.

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