GNES: An Opensource Generic Neural Elastic Search Framework for Searching Everything

Tencent receives tons of text, images and videos everyday. Searching efficiently and effectively means everything to us, and understanding the content is the key to improve the search accuracy. Recent …

Tencent receives tons of text, images and videos everyday. Searching efficiently and effectively means everything to us, and understanding the content is the key to improve the search accuracy. Recent advances in deep learning (VGG/ELMO/BERT) allow one to uniformly represent the content using a dense vector regardless its form (text/video), which forms the backbone of our GNES. But GNES is more than a collection of popular algorithms, it provides an end-to-end solution optimized for user experience, enabling one to easily index, query multiple data types including text and other multimedia formats. Architecture-wise, GNES is an “all-in-microservice” solution that can be easily scaled on cloud services. Apart from the technical highlights, GNES is one of few projects at Tencent that is opensource from the day one. It follows the best-practice outside-in and creates a collaborative culture inside-out. As the lead of GNES, I will share the design principle and lessons learned with you.