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Increasing Desired Search Results with Oak Indexing Analyzer

Adobe Summit 2017 showcased a powerful feature of OAK Indexing that comes with Adobe Experience Manager (AEM) 6.3 with OAK Version 1.6.1.
Oak Index Analyzer provides attributes that help in boosting search to get the desired results. The way it works is that each of the indexes can be defined with analyzer nodes with properties defined on them. When the re-index happens, the analyzer nodes control the way the indexes are created and help the queries fetch more accurate results.


In JCR Query, any full-text search uses the equivalent match for the given word. This may not deliver all the desired results a user wants to see, even though the content is present in the repository. Stemming helps to avoid that by providing a linguistic-like search based on the words given. For example: When stemming is provided on index, the word “sleeve” will fetch results that have words like “sleeved.”
Before applying PorterStem, the search for word “sleeve” fetches five results. It only fetches nodes matching the exact word “sleeve.” See the result in below image.

(Click images to enlarge them)
After applying PorterStem, the search for the same word “sleeve” fetches nine results. It fetches nodes that matches both word “sleeve” and “sleeved.” See the result in below image.


Computer search results will display only the text with an exact match in the full text search. This may not be the desired result for companies to make the end user stay on the website. This technical difficulty is eliminated by the Synonyms configuration on index. In the configuration, we can map two words to be synonymous to each other; when a search is done with one word, it will return combined results for both words.
See the below image for a search of the word “Jacket” before configuration.

See the below image for a search of the word “Jacket” after synonym configuration, which results both “jacket” and “coat.”

Stop Word

In the real world, there are situations where don’t have to index for blacklisted words, thus avoiding them from the search results. Mostly like profanity words. Stop Word configuration on index helps us to do this.
See the below image, assuming the word “retail” as blacklisted word before stop word configuration.

See the below image, assuming the word “retail” as blacklisted word, after Stop Word configuration.

Please leave a comment below if you have any questions on this new feature.

Thoughts on “Increasing Desired Search Results with Oak Indexing Analyzer”

  1. These features are already available in dedicated search systems like Apache Solr, Adobe S&P. Good they are bringing within oak. AEM search query has been a painpoint in projects mandating them to push to external search systems. These features will help to promote oak based search.

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Prakash Venkatesh

Prakash Venkatesh is a certified Adobe Experience Manager and Senior Technical Architect at Perficient. He has successfully delivered software applications for customers across e-commerce, retail, automotive, manufacturing, and product development. He brings a combination of best practices and problem-solving skills to the table with experience gained over years of working in the IT industry.

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