Viktor Sahlström
Aug 22, 2016
  8301
(4 votes)

Episerver Find stemming

One of the things that makes search challenging (and really interesting) is language handling. Often, spoken languages differ from what a programmer is familiar with, since the rules are more comparable to a never-ending set of exceptions than actual rules. To properly analyze a string of text, the system must understand all of these exceptions.

A great feature of Episerver Find is stemming. Stemming reduces an inflected word to its root form (a.k.a. stem), for example, "fishing", "fished", and "fisher" have a root word of "fish." If the root word is determined, it can be used to return the full set of related items, thus improving retrievability and relevancy of search results.

Episerver Find uses snowball stemmers shipped as the default stemmer with Elastic search. This stemmer handles the general rules quite well but does not handle all special cases. In many languages, this works very well (English, for example). But depending on the complexity of the language and the maturity of the stemmer, this is not always enough. Swedish is a case where the default stemmer is not always perfect in execution. Often, the default stemmer creates a conflict that, in turn, causes unexpected search hits.

As an example, consider the Swedish words “bananen” (the banana) and “banans” (the race tracks). Using normal Swedish stemming rules, they would both be stemmed down to “banan.” In this case, any search also stemmed down to “banan” would give both results even though half of them are not relevant.
 
To fix this, a list of exceptions has been added to the Find stemming. We have started with Swedish and will look at additional languages going forward. The new algorithm recognizes that “bananen” and “banans” are different words even though their stem is the same. Hence, it creates unique tokens from them so the search engine can distinguish them at query time. This is a great improvement to search relevancy in many cases. One thing that remains to be solved is the case of “banan” (banana) and “banan” (the race track). In this form, the words are spelled exactly the same and cannot be distinguished without looking at the context. For these cases, search results are returned for both words.

To keep the list updated we would love users and partners to let us know if they find searches that results in weird results. 

Aug 22, 2016

Comments

David Tellander
David Tellander Mar 1, 2017 11:47 AM

Hi Viktor, 

I started a thread in the find forum, before I saw this post, with some examples of words that results in a lot of false positives because of stemming. It seems most of these words gets stemmed to common words that should be stop words according to this snowball stop word list

/David

Per Atle Holvik
Per Atle Holvik Apr 24, 2018 01:53 PM

Hi Viktor,

Is there an exception list for Norwegian? If yes, are you perhaps using this one? http://snowball.tartarus.org/algorithms/norwegian/stop.txt In that case, the search for "oversette" (translate) does not seem to be recognizing "over" as a stop word, at least not in Find 9.6.

/Per Atle

Please login to comment.
Latest blogs
Remote Debugging in Optimizely DXP: What Is Actually Possible?

Introduction At SYZYGY Techsolutions , we support Optimizely DXP projects at scale, so continuously  identifying  the right tools and approaches fo...

Mike | Apr 20, 2026

Removing Unused Properties in Optimizely CMS 13

Learn how to remove orphaned property definitions in Optimizely CMS 13. Explore API updates for IContentTypeRepository and how to safely use...

Stuart | Apr 17, 2026 |

How to Remove the "Paste formatting options" Dialog in Optimizely CMS 12

If you've upgraded from an older Optimizely CMS solution lately, you may have noticed a dialog popping up every time an editor pastes content from...

Henning Sjørbotten | Apr 17, 2026 |

Creating an admin tool - unused assets

Let's make an admin tool to clean unused assets and see how to extend your favorite CMS with custom tools and menues! We will build a tool step by...

Daniel Ovaska | Apr 15, 2026