In this series, we will go over scenarios in which you can use PostgreSQL to create an efficient search engine for full-text searches.
In this article, we will explore how you can refine ranking algorithms for PostgreSQL through using tsvector or a multi-dimensional array.
This article goes over how you can use PostgreSQL to create an efficient search engine for full-text searches and other query types including fuzzy and similarity queries.
The recent update of PostgreSQL 9.6 has made many enhancements in full-text search and has also brought us RUM plug-in support.
This article discusses how you can use PostgreSQL along with ts_stat or MADlib for term frequency and Inverse document frequency analysis.
In this article, we will quickly go over some of the more common scenarios in which you can use PostgreSQL in the hope to inspire you to do more with PostgreSQL.
This article looks at row-level full-text searches in PostgreSQL and walks through how you can create one yourself.
This article shows how PostgreSQL, equipped with both GIN indexes and the cost-based optimizer (CBO), can automatically choose the most optimal query method.
In this article, we look at the location matching filtering syntax of PostgreSQL full-text searches and how you can use this syntax for textual analysis.
This article looks at how you can use PostgreSQL for more efficient searches with split fields.
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