Even with well-tagged documents, there remains the problem of searching for content in the words that appear inside tags. Conventional database query languages and XML-oriented query languages are inadequate by themselves for text searching. Text searching and the user experience are enhanced by combining linguistic processing with XML tags. The query might be refined interactively, based on results. A traditional database enforces a structure on data, so that information can be found and massaged.
Documents present a greater challenge.
This would eliminate a false match when looking for Persian cats. Traditionally, information retrieval uses a different approach, by computing document similarities. A query is treated just like a small document and the query attempts to find the documents most similar to itself. It turns out that the document similarity method does quite well for this kind of query. Whenever we query a document set, we might retrieve irrelevant documents or miss relevant ones.