emphasises the need for intelligent information retrieval techniques. Especially in the rapidlyrngrowing digital libraries and distributed access, it is important to have automatic methods forrnexploring document collections. In this study, the WEBSOM method is used with a quarter ofrncentury of research publications maintained by the International Livestock ResearchrnInstitute for 'this task. The Self-Organizing Map (SOM), also known as Kohonen's featurernmap (a means for automatically arranging high-dimensional statistical data), is used tornposition encoded documents onto a map that provides a general view into the text collection.rnThe general view visualises similarity relations between the documents on a two-dimensionalrnmap display, which can be utilised in exploring the material rather than having to rely onrntraditional search expressions. Similar documents become mapped close to each otherrnproviding an intuitive mechanism and ease of access for maximising the institute's digitalrninformation and knowledge resources particularly for users with limited domain knowledge.rnThis study also sheds some light on the power of the SOM in solving problems of highdimensionalrndata. The trained SOM and the user interface are now usable to both browse therncollection and to automatically map new documents. It can successfully make a distinctionrnbetween the various types of documents and efficiently clusters similar publications to nearrnby locations. It is quite evident that the WEBSOM can effectively visualize the results and isrnthus especially suitable for exploration tasks without the need to come up with searchrnexpressions, which may be difficult even with a rather clear idea of the desired information.rnThe method is a major breakthrough with respect to the much harder problem, for whichrnsearch methods are usually not even expected to offer much support, encountered when therernexists only a vague idea of the object of interest. The same hold true if and when the area ofrninterest resides at the outer edges of one's current knowledge.rnThis full-fledged report presents most of the situations that may be encountered in arnproject that explores the practical application of a WEBSOM method to solve the basicrnproblem of devising a suitable search expression, which could neither leave out relevantrndocuments, nor produce long listings of irrelevant hits. The report also provides the generalrncontext of text retrieval and a detailed discussion on the actual method used in this researchrnin the various sections. The step-by-step procedures and functions used in both encoding therndocument collection (preprocessing), computation of the Kohonen feature map and therndevelopment of the web-based map interface as well as a discussion of the essential resultsrntogether with the codes used are included in the report.