There are several knowledge discovery and analysis issues and questions which the PARIS project would like to address. Some of these were directly related to the main purpose of our efforts; others arose in the course of the project. These include:

• How could we describe conflicts in terms of features or attributes in the most appropriate way?

• Given a data base of well described cases, we are often presented with a new case. Which prior case is most similar to the new case?

• How could we define a good overall distance or proximity measure for conflicts or management/prevention packages?
• Can this measurement approach be extended to more specifically characterized aspects or features of especially related conflicts or conflict management processes?
• How can we compare the different modalities of textually describing, codifying or classifying conflicts?
• After all these issues of comparison and proximity measurement are resolved, we are still faced with classification and clustering issues: How can we most accurately and usefully classify conflicts and cases?
• Can we detect patterns associating conflict attributes and conflict-tools employed by conflict managers?
• How can we proceed when recodifying a large set conflicts in terms of someone else’s conceptual scheme is so terribly costly and time consuming?

To address the above mentioned questions the PARIS project divided itself into subgroups. Since this effort needed an environment to integrate results and resources and make it accessible to other potential users and contributors, we decided to integrate all of our efforts through the construction of a publicly accessible WWW Web site.

In a general way, the PARIS project tries to classify and cluster international conflicts and conflict prevention efforts on the basis of information assembled in different databases. It has sought to apply versions of case-based reasoning techniques to suggest ways of decreasing the level of violence in emergent or ongoing violent conflicts. In contrast to the other preliminary explorations of the utility of knowledge discovery techniques like C4.5, we have not be interested in merely describing different patterns in our data such as "What is the pattern of participation of US, USSR and China in Third World conflicts? " PARIS has a more specific and heuristic conflict prevention focus: we have tried to gear our analyses to preventively oriented concerns, to the discovery of actions which conflict managers or preventers have taken, or could have taken, to prevent violence escalation and encourage violence diminution. Our exploration and development of KDD techniques is defined through such lenses.

In particular, there are 3 approaches to Knowledge Discovery from Databases which we are exploring within the PARIS project and which we want briefly to describe here. Even though each of these approaches has only been preliminarily explored, we are sufficiently encouraged by our results to wish to proceed further down these paths of inquiry. We encourage our browsers to refer to forthcoming papers for further details and results