This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information,
and querying them in terms of topics and topic relationships. We propose a model for web information resources, and a query
language SQL-TC (Topic-Centric SQL) to query the model. The model is composed of web-based information resources (XML or HTML
documents on the web), expert advice repositories (domain-expert-specified metadata for information resources), and personalized
information about users (captured as user profiles, that indicate users’ preferences as to which expert advice they would
like to follow, and which to ignore, etc).
The query language SQL-TC makes use of the metadata information provided in expert advice repositories and embedded in information
resources, and employs user preferences to further refine the query output. Query output objects/tuples are ranked with respect
to the (expert-judged and userpreference-revised) importance values of requested topics/metalinks, and the query output is
limited by either top n-ranked objects/tuples, or objects/tuples with importance values above a given threshold, or both.