{"id":724090,"date":"2021-02-08T12:33:40","date_gmt":"2021-02-08T20:33:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=724090"},"modified":"2021-02-08T12:33:40","modified_gmt":"2021-02-08T20:33:40","slug":"proceedings-of-the-first-workshop-on-natural-language-interfaces","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/proceedings-of-the-first-workshop-on-natural-language-interfaces\/","title":{"rendered":"Proceedings of the First Workshop on Natural Language Interfaces"},"content":{"rendered":"

Natural language interfaces (NLIs) have been the “holy grail” of human-computer interaction and
\ninformation search for decades. However, early attempts in building NLIs to databases did not achieve the
\nexpected success due to limitations in language understanding capability, extensibility and explainability,
\namong others. The last 5 years have seen a major resurgence of NLIs in the form of virtual assistants,
\ndialogue systems, and semantic parsing and question answering systems. The horizon of NLIs has also
\nbeen significantly expanding beyond databases to, e.g., knowledge bases, robots, Internet of Things, Web
\nservice APIs, and more.<\/p>\n","protected":false},"excerpt":{"rendered":"

Natural language interfaces (NLIs) have been the “holy grail” of human-computer interaction and information search for decades. However, early attempts in building NLIs to databases did not achieve the expected success due to limitations in language understanding capability, extensibility and explainability, among others. The last 5 years have seen a major resurgence of NLIs in 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