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[Our] challenge was around defining what level of specificity would consistently give the right match for a response.The sessions were a unique challenge; with 130 sessions that often had similar keywords in the title (for instance, four different sessions had the term “future of” in their titles) we had to match with enough fidelity so as not to pull up every session with a certain keyword, but it [also] couldn’t be so rigid that people would have to remember exact session titles in order to get a match.(Just don't expect to get many words in edgewise.) " data-title = "Can’t Get a Creative Recruiter to Call You Back?No Worries, There’s a Bot for That" data-categories = "adfreak" data-popup = "" data-ads = "Yes" data-company = "[]" data-outstream = "yes" get the recruiter's name and it's like trying to decrypt the Riddle of the Sphinx just to get them to look at you.Natural language processing is a challenge that technologists have been working on for decades. It’s less dependable because in order to make Siri understand such a range of open-ended requests, it has to pull in from databases that are so large they can’t be hardcoded in.For this chatbot, we started by building on top of the existing natural language platform offered by and elasticsearch.

Some online chatbots won't show up in mobile browsers.

To get to that greater specificity, we set a threshold for a match in the elasticsearch: a certain number of words in any session title would have to match the number of words in the query to get a match.

However, words like “the,” “and,” or “is” were also factoring into that match threshold, which could be part of how the question is phrased and not the session itself, [so] we decided to add another layer of keyword matching on top of the elasticsearch, which was based on exact keyword phrases.

These phrases were identified by [real] people–including feedback from the broader Work & Co team on how they might search–so that we were accommodating for the way a human might recall a session [like the one we hosted, titled] “Work & Co on Timelessness: What Digital Designers Can Learn from Vignelli, the Eameses, and Mies van der Rohe.”All of this combined gave us a much greater accuracy of matching the session a user was actually looking for.

Pop culture these days is awash in tales of AI run amok, from machines that act like humans to humans in love with machines.


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