CCReSD: concept-based categorisation of Hidden Web databases

Hidden Web databases dynamically generate results in response to users' queries. The categorisation of such databases into a category scheme has been widely employed in information searches. We present a Concept-based Categorisation over Refined Sampled Documents (CCReSD) approach that effectively handles information extraction, summarisation and categorisation of such databases. CCReSD detects and extracts query-related information from sampled documents of databases. It generates terms and frequencies to summarise database contents. It also generates descriptions of concepts from their coverage and specificity given in a category scheme. We conduct experiments to evaluate our approach and to show that it assigns databases with more relevant subject categories.