Keymantic: A Keyword-based Search Engine using Structural Knowledge

Traditional techniques for query formulation need the knowledge of the database contents, i.e. which data are stored in the data source and how they are represented. In this paper, we discuss the development of a keyword-based search engine for structured data sources. The idea is to couple the ease of use and flexibility of keyword-based search to the large amount of knowledge derived from data structures, to help the user with metadata extracted from extensional data and to translate keywords into SQL statements, in order to exploit the power of traditional DBMS engines. Our solution should be effective, semantic-based, and applicable also when instance are not continuously available, such as in integrated data sources or in data sources extracted from the deep web.