Search relevance engineering consists of query understanding processes and customized ranking with historical engagement information.
Query understanding is the process of inferring the intent of the search keyword by extracting semantic meaning from the search query. Query understanding methods generally take place before the search engine retrieves and ranks results. It’s all about what happens before the search query is generated. Customized ranking is derived with scores like textual relevancy, past engagement score, past conversions, and geographical trends.
In this presentation Dipak Parmar, Principal Engineer at Shipt Inc. will talk about each of the above steps and how they can be helpful to improve the overall search experience. We will also discuss architectures behind building relevancy pipeline, services with Elasticsearch, a Painless script in Elasticsearch for ranking and how we can evaluate the experiments. He will also give an overview of how Shipt’s search platform is developed as a case study.
Hosted by Charlie Hull of OSC with an associated Q&A session with our speaker.
Picture from Question Vectors by Vecteezy
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