The marketing manager for American Cities wants to add search to their domain americancities.com. Within minutes, all pages on the domain were indexed.
Jane heads to the website www.americancities.com to conduct some research for her upcoming vacation to San Francisco. She types in her query “san fram hotels” but doesn’t realize she has misspelled the keyword “fran”.
A query pipeline receiving the query “san fram hotels” will predict the word “fram” is likely incorrect. Alternatives that are spelled correctly and highly probable to match the user intent will be added into the query automatically. This alternate query is then weighted based on it's probability to be the correct alternative when ranking search results.
In the pipeline, a synonym has been set where every query for “san fran” relates exactly to the keywords “san francisco”.
This creates the query “san francisco hotels” and keeps the original query “san fram hotels”. “san francisco hotels” is determined to more likely lead to a better search result.
One particular result, titled “The San Francisco City Cheap Hotel Deals”, is the most popular when users search for “san francisco hotels”. When this query leaves the pipeline and the best results are returned, this result will be boosted.
In the americancities.com search index, there is a boost rule where results that contain /cheap-hotels/new-york/ in the URL are to be boosted by 20%. Results that match this boost rule will be lifted higher in the results set.
The end user is given a list of results, determined from most relevant to least relevant. Jane clicks on the top result, “The Best San Francisco Cheap Hotel Deals”, and finds a place to stay in "San Fran".