Intelligent data analysis for conservation: experiments with rhino horn fingerprint identification
Conservation is an area in which a great deal of data has been collected over many years. Intelligent Data Analysis offers the possibility of analysing this data in an automatic fashion to map characteristics, identify trends and offer guidance for conservation action. This paper is concerned with the use of techniques of Intelligent Data Analysis for an important task in animal conservation: the identification of the species and origin of illegally traded or confiscated African rhino horn. It builds on an earlier analysis by the African Rhino Specialist Group. It is demonstrated that it is possible to distinguish between both species and country of origin with a high degree of accuracy and that the results are also likely to be suitable for use in court.
intelligent data analysis conservation rhino horn fingerprint identification data mining neural nets automatic rule induction decision trees