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System Architect Go
System Architect Go
Nov 2, 2020 · Backend Development

Custom Scoring in Elasticsearch Using function_score

Elasticsearch calculates a relevance score for each document, but using the function_score query you can customize this scoring by combining the original query_score with a user-defined func_score through various functions such as weight, random_score, field_value_factor, decay_function, and script_score, allowing flexible ranking based on business needs.

Backendcustom scoringelasticsearch
0 likes · 11 min read
Custom Scoring in Elasticsearch Using function_score
Tencent Cloud Developer
Tencent Cloud Developer
Jul 22, 2020 · Backend Development

Practical Optimization of Elasticsearch Search Ranking

The article explains how to systematically improve Elasticsearch search relevance by fine‑tuning Query DSL with filters, phrase matching, and boosts, incorporating static scoring via function_score, adjusting BM25 similarity parameters, and using diagnostics like _explain to iteratively achieve higher ranking quality.

BM25BoostQuery DSL
0 likes · 17 min read
Practical Optimization of Elasticsearch Search Ranking
Ctrip Technology
Ctrip Technology
Jun 29, 2017 · Backend Development

Understanding Elasticsearch Scoring: Lucene Scoring Functions, Query Boosting, and Function Score Queries

This article explains how Elasticsearch computes relevance scores using Lucene's practical scoring formula, term frequency, inverse document frequency, field-length norms, and query normalization, and demonstrates query-time boosting, constant_score, function_score, decay functions, and script_score with practical DSL examples.

LuceneQuery BoostingScoring
0 likes · 14 min read
Understanding Elasticsearch Scoring: Lucene Scoring Functions, Query Boosting, and Function Score Queries