Traditional search mainly compares the words entered with the visible text of a find report. Semantic search extends this process. It creates a structured profile from the query and compares it with the available AI object profiles of active finds. The recognised primary object, synonyms, related objects, subgroups, broader groups and important search terms may all contribute. A search for “couch” can therefore match a find described as a “sofa”. Semantic analysis supplements normal search; it does not replace filters or the user’s final review.
Start with a clear object term.
Add important properties such as material, colour or item type.
Review results that use different but related wording.
Use category and location filters if the result list is too broad.