In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
Community QA portals provide an important resource for non-factoid question-answering. The inherent noisiness of user-generated data makes the identification of high-quality cont...
Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...