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Keyword queries offer a convenient alternative to traditional SQL in querying relational databases with large, often unknown, schemas and instances. The challenge in answering such queries is to discover their intended semantics, construct the SQL queries that describe them and used them to retrieve the respective tuples. Existing approaches typically rely(More)
We propose the demonstration of Keymantic, a system for keyword-based searching in relational databases that does not require a-priori knowledge of instances held in a database. It finds numerous applications in situations where traditional keyword-based searching techniques are inappli-cable due to the unavailability of the database contents for the(More)
One of the most important feature of a MAS (Multi-Agent System) is the cooperation and the coordination among agents placed in distributed environments. Due to the high heterogeneity of agents and platforms, interoperability has become a key issue for the use of MASs in academic and industrial fields. Several approaches to interoperability proposed so far(More)
In this paper we describe Keymantic, a framework for translating keyword queries into SQL queries by assuming that the only available information is the source metadata, i.e., schema and some external auxiliary information. Such a framework finds application when only intensional knowledge about the data source is available like in Data Integration Systems.