Poelmans, JonasElzinga, PaulViaene, StijnDedene, Guido (+)Van Hulle, Marc2017-12-022017-12-022009978-3-642-02396-510.1007/978-3-642-02397-2_28http://hdl.handle.net/20.500.12127/3192Topographic maps are an appealing exploratory instrument for discovering new knowledge from databases. During the recent years, several variations on the Self Organizing Maps (SOM) were introduced in the literature. In this paper, the toroidal Emergent SOM tool and the spherical SOM are used to analyze a text corpus consisting of police reports of all violent incidents that occurred during the first quarter of 2006 in the police region Amsterdam-Amstelland (The Netherlands). It is demonstrated that spherical topographic maps provide a powerful instrument for analyzing this dataset. In addition, the performance of the toroidal Emergent SOM is compared to that of the spherical SOM, and it turned out to be superior to that of an ordinary classifier, applied directly to the data.enBusiness IntelligenceLecture notes in Computer Science51528140610141017141252763213657