The results are usually sorted according to an internal scoring mechanism using fuzzy query processing techniques. The score is an indication of the relevance of the document which can be affected by many factors. The phonetic difference between the search term and the hit is one of the most important factors. Some fields are boosted so that hits within these fields are more relevant to the search result as hits in other fields. Also, the distance between query terms found in a document can play a role in determining its relevance. E.g., searching for “John Smith”, a document containing “John Smith” has a higher score than a document containing “John” at its beginning and “Smith” at its end. Furthermore, search terms can be easily augmented by searches with synonyms. E.g., searching for “car” retrieves documents with the term “vehicle” or “automobile” as well. This opens the door for ontological searches and other semantically richer similarity searches.