Human resources management aims at achieving the principle of the right place, the right person. A Human Resources Information Systems support the principle by providing various information about the personnel resource database and facilitating the selection of relevant candidates. From an information system's view, such a selection process can be characterized as an repetitive and knowledge-intensive query answering process at the personnel resource database. However, since most of the human resource information systems are built on conventional database systems that lack the intelligent features required in the personnel selection process, the query answering often yield unsuccessful results.
To overcome limitations of existing human resource information systems, this paper proposes a cooperative query processing model that embeds the intelligent feature of human experts into a database system. Cooperative query answering consists of analyzing the intent of the query and providing generalized neighborhood or associated information relevant to the query. The model in this paper is composed of a knowledge base about personnel data and a cooperative query processor. The knowledge base manages the knowledge about the classification of the data. When a query is submitted, the cooperative query processor transforms the query using the knowledge in the knowledge base and provides meaningful answers such as exact, or approximate and associated ones.
