Continue reading Exact matches for short search terms

Exact matches for short search terms

Is is possible to set Relevanssi in a way that it would return only perfect matches for queries up to 3 characters, but any words that starts with the queried term if it has 4 characters or more? – Originally asked here Yes, but it requires a bit of code. Add this to your site and…

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Continue reading Wildcard matching

Wildcard matching

Relevanssi Premium 2.10.2 introduces a new way to search: wildcard matching. Once the wildcard matching is enabled (it is disabled by default), it introduces two new operators: * and ?. Using the wildcard operators The * operator replaces zero or more characters, so searching for w*ess would match “wilderness”, “witness”, “WordPress” and also “wess”. The…

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Continue reading Relevanssi and languages

Relevanssi and languages

Relevanssi is language-agnostic in itself. It does not know any language and doesn’t care about which language the site uses. However, there are a few things that you need to consider when using Relevanssi in languages other than English. Characters: use UTF8 As long as your site uses UTF8 characters, Relevanssi can handle just about…

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Continue reading Indexing only attributes from shortcodes

Indexing only attributes from shortcodes

I need to add some custom shortcodes to the list of the “removed” ones (so they don’t show in plain text in the results). However, some of them are built like [shortcode_name text=”Need to keep this in results”] and I would like the content in the text parameter to stay in the results. How do I go about this?…

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Continue reading Boosting shorter posts with higher keyword density

Boosting shorter posts with higher keyword density

By default, Relevanssi tends to prefer longer posts. The default TF × IDF weights Relevanssi uses simply count the term frequency, ie. how many times a word appears in the post. That prefers longer posts as they usually have the search term appear more often. However, a 500-word post with 15 search term appearances might…

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Continue reading WooCommerce: Return only exact matches for SKU searches

WooCommerce: Return only exact matches for SKU searches

This little filter function works on relevanssi_hits_filter. When a search query is made that matches an SKU (or any other custom field, but SKUs are the most likely scenario here), only results that match the SKU will be returned. For this to work, Relevanssi must be set to index the _sku custom field (because otherwise,…

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Continue reading Using phrases in Related posts searches

Using phrases in Related posts searches

I have a book review site where I’m using Relevanssi Premium and the Related posts to highlight related book reviews. The reviews have multiple taxonomies used for the related posts: tags, book author, series, characters, and places. Messy relations The problem is, with the default settings, the Related posts get a bit messy. This site…

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Continue reading Relevanssi indexes excluded posts

Relevanssi indexes excluded posts

Sometimes it can happen the search results include posts from a post type that has been excluded from the index. When that happens, here are things you can check. Are you using Relevanssi? It’s possible your search results are not coming from Relevanssi. The quickest way to check is to use the Relevanssi admin search…

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Continue reading Indexing product codes with and without spaces

Indexing product codes with and without spaces

A Relevanssi Premium customer had a problem with product codes. The codes are in the format “ABC 100”, a group of letters and digits with a space in between. Users may search for the codes without the space, so the post should be found with “ABC 100” or “ABC100”. The product codes don’t appear in…

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Continue reading Debugging indexing problems

Debugging indexing problems

The easiest way to debug indexing problems is to use the WP CLI tools available in Relevanssi Premium. To see how Relevanssi sees the post 123, just use the following command on the command line: This will print out how Relevanssi sees the post, how it appears in the different steps of the indexing process…

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