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Wednesday, October 17 • 5:05pm - 5:45pm
How to Build a Semantic Search System

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Building a semantic search system - one that can correctly parse and interpret end-user intent and return the ideal results for users’ queries - is not an easy task. It requires semantically parsing the terms, phrases, and structure within queries, disambiguating polysemous terms, correcting misspellings, expanding to conceptually synonymous or related concepts, and rewriting queries in a way that maps the correct interpretation of each end user’s query into the ideal representation of features and weights that will return the best results for that user. Not only that, but the above must often be done within the confines of a very specific domain - ripe with its own jargon and linguistic and conceptual nuances.

This talk will walk through the anatomy of a semantic search system and how each of the pieces described above fit together to deliver a final solution. We'll leverage several recently-released capabilities in Apache Solr (the Semantic Knowledge Graph, Solr Text Tagger, Statistical Phrase Identifier) and Lucidworks Fusion (query log mining, misspelling job, word2vec job, query pipelines, relevancy experiment backtesting) to show you an end-to-end working Semantic Search system that can automatically learn the nuances of any domain and deliver a substantially more relevant search experience.

avatar for Trey Grainger

Trey Grainger

SVP of Engineering, Lucidworks
Trey is the SVP of Engineering at Lucidworks, where he leads their engineering efforts around Lucidworks Fusion, Apache Lucene/Solr, and their other open source and commercial offerings. Trey is also the co-author of the book Solr in Action, as well as a published researcher and frequent... Read More →

Wednesday October 17, 2018 5:05pm - 5:45pm EDT
Salon 4&5