How Can I Prioritize Relevance in MySQL Full-Text Searches Across Multiple Columns?

Prioritizing Relevance in MySQL Full Text Search with Multiple Columns

In MySQL, the MATCH() AGAINST() function facilitates full-text searches across multiple columns. By default, search relevance is determined by the combined occurrence of matching terms in all specified columns. However, you may encounter scenarios where you need to prioritize relevance based on specific columns.

Relevance by Column

To achieve this, you can introduce multiple relevance columns, one for each column, as you mentioned. While this approach ensures accurate prioritization, it also implies redundant searches, affecting performance.

Optimizing Relevance Prioritization

An alternative method that balances performance and relevance prioritization is to adjust the relevance calculation formula. Here's a modified query that incorporates a weight coefficient for the head column:

SELECT * ,
       MATCH (head, body) AGAINST ('some words') AS relevance,
       MATCH (head) AGAINST ('some words') AS title_weight
FROM pages
WHERE MATCH (head, body) AGAINST ('some words')
ORDER BY (title_weight + relevance) DESC

This query assigns a higher weight to the relevance score of the head column. By adjusting the weight accordingly, you can prioritize relevance based on specific columns.

Bonus: Counting Word Occurrences

To count the occurrence of matching terms within each column, you can utilize the BOOLEAN MODE flag in MATCH():

SELECT * ,
       MATCH (head, body) AGAINST ('some words' IN BOOLEAN MODE) AS relevance,
       MATCH (head) AGAINST ('some words' IN BOOLEAN MODE) AS title_count
FROM pages
WHERE MATCH (head, body) AGAINST ('some words' IN BOOLEAN MODE)
ORDER BY title_count DESC, relevance DESC

The title_count column indicates how many times the specified terms erscheinen in the head column. This information aids in refining your search results further.

Note: This approach is suitable for MySQL versions 8.0 and above. For older versions, you may need to explore alternative methods for prioritizing relevance and counting term occurrences.

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