The searches defined by Boolean operators are literal searches -- the engine looks for the words or phrases exactly as they are entered. This can be a problem when the entered words have multiple meanings. "Bed," for example, can be a place to sleep, a place where flowers are planted, the storage space of a truck or a place where fish lay their eggs. If you're interested in only one of these meanings, you might not want to see pages featuring all of the others. You can build a literal search that tries to eliminate unwanted meanings, but it's nice if the search engine itself can help out.
One of the areas of search engine research is concept-based searching. Some of this research involves using statistical analysis on pages containing the words or phrases you search for, in order to find other pages you might be interested in. Obviously, the information stored about each page is greater for a concept-based search engine, and far more processing is required for each search. Still, many groups are working to improve both results and performance of this type of search engine. Others have moved on to another area of research, called natural-language queries.
The idea behind natural-language queries is that you can type a question in the same way you would ask it to a human sitting beside you -- no need to keep track of Boolean operators or complex query structures. The most popular natural language query site today is AskJeeves.com, which parses the query for keywords that it then applies to the index of sites it has built. It only works with simple queries; but competition is heavy to develop a natural-language query engine that can accept a query of great complexity.
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