Providing Useful Suggestions to Misspelled Queries with Did You Mean

Did You Mean assists users with a high relevance suggestion when they misspell.

Fig. 1

 

The feature is advanced in the sense that it works with all supported languages—including Mandarin, Russian, and French—and can be taught in-house terminology. An example of in-house terminology at work is in Fig. 1, where Did You Mean suggests "searchunify" instead of "search" and "unify." Admins can expand the default Did You Mean dictionary by adding such corporate jargon, technical terminology, and other terms in bulk or one at a time.

Advantages

  • Jargon Recognition. In-house terminology, customer and employee names are recognized and never "corrected". Instead of asking a search if he meant "Osama Dazai" when he was actually looking for Japanese author "Osamu Dazai", Did You Mean recognizes the name as long as it is stored somewhere in the Custom Dictionary.
  • Guaranteed Results. Each suggestion has at least one matching document if a search client is connected to all the content sources from which the suggestions are extracted. It never happens that a user clicks on a suggestion and is greeted with a "No Results Found" message.
  • Synonym Recognition: Keywords—including jargon, abbreviations, and initialisms—set as synonyms are never tinkered with. If you set up "enzootic cycle" and "EnC" as synonyms then a search for "EnC" will find results for "enzootic cycle" and Did You Mean will not make any attempt to correct "EnC."
  • Dictionary Recognition. There are a some minor differences between the English and American orthography. Whereas an American will "plow" in four letters an Englishman will go on for another two characters to "plough". The "jailer" in America is nothing like the "gaoler" in England. SearchUnify recognizes these differences is not triggered by any of those queries. Ite has been designed to recognize multiple correct variants of a query.

Adding Data to Did You Mean

  1. Go to NLP Manager and then open Did You Mean .

In Bulk

  1. Select a Content Source, Content Type, and Content Field, and then Add.

  2. A row is inserted in the table on Add. Save your settings.

Click Train Dictionary to include the newly-added data into your instance's Did You Mean dictionary.

One Term at a Time

  1. Scroll down to Custom Dictionary and click Edit Dictionary.

  2. Add new terms—one on each line—and after the last term, press Enter to generate an empty last line. When there is no empty line at the end of the list turns to . When the Save icon is yellow, an admin cannot add new terms to Custom Dictionary.

  3. Click to add the terms to Custom Dictionary.

Custom Dictionary after the update. Now anyone who searches runs a search with "sarchunify" or "searchunfy" or another misspelling, the search client will throw a suggestion: Did You Mean: searchunify

Last updated: Friday, February 26, 2021

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