Abstract
We present an end-to-end system for open-domain non-factoid question-answering. To accomplish this we leverage the information on the ever-growing World Wide Web, and the capabilities of commercial search engines to find the relevant information. Our QA system is composed of three components: (i) query formulation module (QFM) (ii) candidate answer generation module (CAGM) and (iii) answer selection module (ASM). A thorough empirical evaluation using two datasets demonstrates that the proposed approach is highly competitive.
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Khvalchik, M., Pithyaachariyakul, C., Kulkarni, A. (2017). Answering the Hard Questions. In: Gracia, J., Bond, F., McCrae, J., Buitelaar, P., Chiarcos, C., Hellmann, S. (eds) Language, Data, and Knowledge. LDK 2017. Lecture Notes in Computer Science(), vol 10318. Springer, Cham. https://doi.org/10.1007/978-3-319-59888-8_22
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