How emergent self organizing maps can help counter domestic violence.

Topographic maps are an appealing exploratory instrument for discovering new knowledge from databases. During the past years, new types of Self Organizing Maps (SOM) were introduced in the literature, including the recent Emergent SOM. The ESOM is used to study a large set of police reports describing a whole range of violent incidents that occurred during the year 2007 in the police region Amsterdam-Amstelland (the Netherlands). It is demonstrated that it provides an exploratory search instrument for examining unstructured text in police reports. First, it is shown how the ESOM was used to discover a whole range of new features that better distinguish domestic from non-domestic violence cases. Then, it is demonstrated how this resulted in a significant improvement in classification accuracy. Finally, the ESOM is showcased as a powerful instrument for the domain expert interested in an indepth investigation of the nature and scope of domestic violence.

The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research