This is a guest post by Audrey Boguchwal of Samasource, Quid’s longtime business partner in our company data acquisition pipeline. It was originally published here to showcase how Samasource’s web research and data cleaning services help collect data for Quid to build our natural language processing-powered data platform. How does Quid create business intelligence? Here […]
Our First Engineering Game Day
Chaos Engineering ideas are gathering steam these days. In August we ran an engineering-wide Game Day here at Quid, where we simulated real-world service failures and had “on-call teams” exercise their incident response skills. It was great fun and good training for Quid engineers. This post covers the organizational side of Game Day, lessons learned, and some technical tricks that others can use in similar exercises.
Improving search with Word2Vec and Wikipedia
Quid wants to show you the most relevant results when you perform a search. A part of the job of our search is to get the most signal from each term. Ben Bowles, a resident data scientist, describes an ongoing experiment for using related terms to help users get more relevancy: Sometimes users have a […]
Managing text data you haven’t seen and can’t control
There is a lot that you need to predict, and a lot that can go wrong, when working with text data you have little control over. In this post the Quid technology team explores the methodologies used when addressing these challenges. By: Vincenzo Ampolo, Ashkan Zadeh, Fabio Ciulla, Mark Longo, Ruggero Altair Tacchi This […]
Using deep learning with small data
Quid maintains an incredibly diverse set of company descriptions. A priority for Quid is identifying company descriptions of poor quality and improving them before they even get into our index. Ben Bowles, a resident data scientist, wrote up a great article featured on our parent blog on our approach to separating the “good” from the […]