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DESCRIPTION:Click for Latest Location Information: http://smartdata2015.dataversity.net/sessionPop.cfm?confid=91&proposalid=7642\nThe usual focus when developing Virtual Assistants and analyzing their dialogs with human users, is on what the VAs say and how to make their part of the conversation as human-like as possible. In this session we want to bring more light into the human side of the conversation and focus on learning as much from it as possible.\nWe will present how we:\nDesigned and implemented a flexible and extensible query language, specialized for real-time analysis of NLI dialogs  \nMine large numbers of VA dialogs for information about the participants, their profiles, opinions, motives and behavior  \nUse machine-learning to integrate both automatic improvements and semi-automatic improvement recommendations into the VA development cycle  \nCombine rule-based and statistical methods to enable free-form, natural language querying of natural language data \nWe will approach these topics from a pragmatic angle and share our experience on tackling the specific challenges of dialog NL data. The key points will be relevant and valuable independently of the concrete NLI platform that we have developed.  The focus will lie on the iterative nature of the NLI application development and how the data produced by the application can feed the further application development.
DTSTART:20150819T114500
SUMMARY:She Said, It Said… - How We Learn From Dialogs Between Humans and Virtual Assistants
DTEND:20150819T122959
LOCATION: See Description
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