Current search engines return a ranked list of web pages represented by page excerpts called the web snippets. The ranking is computed according to some relevance criterium that takes into account textual and hyperlink information about the web pages (see e.g. [1]). This approach is very well-known and a lot of research is pushing towards the design of better and faster ranking criteria. However, it is nowadays equally known that a flat list of results limits the retrieval of precise answers because of many factors. First, the relevance of the query results is a subjective and time-varying concept that strictly depends on the context in which the user is formulating the query. Second, the ever growing web is enlarging the number and heterogeneity of candidate query answers. Third, the web users have limited patience so that they usually just look at the top ten results. The net outcome of this scenario is that the retrieval of the correct answer by a standard user is getting more and more difficult, if not impossible.
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