Search at Quid is recognized as one of the most valuable yet challenging areas within our product. It serves as the vehicle through which our users first engage with the product, and also serves as an integral part in helping our users derive insight. The results from a user search are fed to both our network generation and clustering algorithms, as well as the beautiful visualizations described in previous blog posts. Suggested terms are just one of the ways we enhance the search experience for our users, enabling the creation of more complex queries faster. This post will be the first in a series of blogs highlighting some of the unique challenges faced by Quid’s Platform Search team. In this post we will give a brief peek into how we approach suggested terms at Quid. The Use Case Every search engine these days, from Facebook to Google, provides some form of suggestions. Users have come to both expect and rely on this functionality as an extension of search. For Quid, this meant let’s not reinvent the wheel, but let’s also make sure our suggestions serve the correct function within our application. Our use case involved solving for the following: * Low […]Read More
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