Neural Information Retrieval and Conversational Question Answering: One the main affordances of conversational UIs is the ability to use natural language to succinctly convey to a bot what you want. An area where this interface excels is in question answering (Q&A). Research into Q&A systems often falls at the intersection of natural language processing (NLP) and information retrieval (IR), and while NLP has been getting a lot of attention from deep learning for several years now, it’s only largely within the last year or so that the field of IR has seen an equivalent explosion of interest in employing these techniques. In this presentation, I will touch on challenges facing conversational bots, provide a high level overview into the emerging field of Neural Information Retrieval, discuss how these methods can be used in a Q&A context, and then highlight some lessons learned attempting to design and deploy a conversational Q&A agent-based product.
Session Summary
Neural Information Retrieval and Conversational Question Answering
MLconf 2017 Seattle
Byron Galbraith
Talla
Chief Data Scientist
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