  The last few years have seen an explosion of research on the topic of
automated question answering (QA), spanning the communities of information
retrieval, natural language processing, and artificial intelligence. This
tutorial would cover the highlights of this really active period of growth for
QA to give the audience a grasp over the families of algorithms that are
currently being used. We partition research contributions by the underlying
source from where answers are retrieved: curated knowledge graphs, unstructured
text, or hybrid corpora. We choose this dimension of partitioning as it is the
most discriminative when it comes to algorithm design. Other key dimensions are
covered within each sub-topic: like the complexity of questions addressed, and
degrees of explainability and interactivity introduced in the systems. We would
conclude the tutorial with the most promising emerging trends in the expanse of
QA, that would help new entrants into this field make the best decisions to
take the community forward. Much has changed in the community since the last
tutorial on QA in SIGIR 2016, and we believe that this timely overview will
indeed benefit a large number of conference participants.
