the importance of prior probabilities for entry page search
An important class of searches on the world-wide-web has the goal to find an entry page (homepage) of an organisation. Entry page search is quite different from Ad Hoc search. Indeed a plain Ad Hoc system performs disappointingly. We explored three non-content features of web pages: page length, number of incoming links and URL form. Especially the URL form proved to be a good predictor. Using URL form priors we found over 70\% of all entry pages at rank 1, and up to 89\% in the top 10. Non-content features can easily be embedded in a language model framework as a prior probability.
prior probabilities probability entry page search paging search class systems feature web page links urls ranking embedding language models  framework  contention parameter estimation world wide web ad-hoc