7 Interpreting query intent through semantic search

 

This chapter covers

  • The mechanics of query interpretation
  • Implementing an end-to-end query intent pipeline to parse, enrich, transform, and search
  • Tagging and classifying terms and phrases in queries
  • Augmenting queries with knowledge graph traversals
  • Interpreting semantics of domain-specific query patterns

In chapters 5 and 6, we leveraged content and signals to interpret the domain-specific meaning of incoming user queries. We discussed phrase identification, misspelling detection, synonym discovery, query intent classification, related terms expansion, and even query-sense disambiguation. We’ve mostly discussed these techniques in isolation to demonstrate how they each work independently.

In this chapter, we’ll put all those learnings into practice, integrating previous techniques into a unified query interpretation framework. We’ll show an example search interface that accepts real queries, interprets them, rewrites them to better express the end user’s intent, and then returns ranked results.

7.1 The mechanics of query interpretation

 

7.2 Indexing and searching on a local reviews dataset

 
 

7.3 An end-to-end semantic search example

 
 
 

7.4 Query interpretation pipelines

 
 
 
 
 
 
 
 
 

7.4.4 Searching with a semantically enhanced query

 
 
 

7.5 Summary

 
 
 
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