  The existing search engines sometimes give unsatisfactory search result for
lack of any categorization of search result. If there is some means to know the
preference of user about the search result and rank pages according to that
preference, the result will be more useful and accurate to the user. In the
present paper a web page ranking algorithm is being proposed based on syntactic
classification of web pages. Syntactic Classification does not bother about the
meaning of the content of a web page. The proposed approach mainly consists of
three steps: select some properties of web pages based on user's demand,
measure them, and give different weightage to each property during ranking for
different types of pages. The existence of syntactic classification is
supported by running fuzzy c-means algorithm and neural network classification
on a set of web pages. The change in ranking for difference in type of pages
but for same query string is also being demonstrated.
