Presently, the search queries that we enter (even with the Boolean operators) are ‘literal’ searches. The search engine looks exactly for the words and phrases specified in the query. This usually works well for most of our present needs. Sometimes however, words and phrases can have multiple meanings. Our query then does generate results literally related to what we were looking for but not conceptually related at all. To get results that are conceptually related to what you are looking for (and not just literally), you can build a literal search using Boolean operators to remove unwanted meanings, but it would be pretty neat if the search engine could do that for us.
This brings us to a crucial and interesting field of search engine research called concept-based searching. This involves things like statistical analysis on pages containing the words you queried to see if they are the concept you were looking for. Obviously, the information that needs to be stored in each page will be greater for a concept based search and much more processing will be required.
Another area of research is called natural-language queries. This is an interesting idea which involves providing a search engine with a search query in the form of a question that you might have asked someone sitting next to you. There is no need for Boolean operators or complex query structures. AskJeeves.com is the closest to this kind of a search engine and it works for simple queries. Yet there is tremendous competition to develop natural language query engines that can accept a query of more complexity.
