In each query session, the algorithm maintains weights on the data in the database which reflect the assumed relevance of the data. Relevance feedback is used to modify these weights. As a second ingredient, the algorithm uses a minimax principle to select data for presentation to the user: any response of the user will provide significant information about his query, such that relatively few feedback rounds are sufficient to find a satisfactory data. We have implemented this algorithm and have conducted experiments on both simulated data and real data which show promising results. The objective behind developing IMPRO (Industrial Manpower Resource Organizer) is to maintain the hierarchy of the employees within an organization. It provides the manger and administrative department an overall hierarchical view of the complete enterprise and helps them in managing employee’s allocation between the manufacturing plants in large scale industry. Every Organization has many managers, who are responsible for all the activities in the organization. These managers manage different aspects of the organizational management issues, such as manufacturing, production, Marketing, etc; one such essential management issue is IMPRO. As years progressed, the approach of the management changed towards the human capital. Now Hierarchical Organization is part of every organization, and has its own identity and importance.

Content Based, Data Retrieval, Manpower, IMPRO, Feature Selection

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