Search engines have come a long way since the early days of reliance on information retrieval as user intent drives modern search applications.  Businesses driven by search like eCommerce, content-based companies lose a small but decent amount of traffic to queries getting a lower number of impressions/clicks/conversions as few or irrelevant results are computed and shown. This session focus on identifying poor/low performing queries and terms using Head and Tail Analysis, classify with potential reasons and suggest corrections or improved query models for them. The session concludes with emphasizing on experiments being vital to the entire process of improving search relevance. The session is based on Head-n-Tail Analysis in Fusion 4 by Chao Han, VP Head of Research, Lucidworks.

This talk is presented by Lucidworks.