This research explored the applicability of WEBSOM (Web Based Self Organizing map) for retrieving textsrnwritten in Amharic language . The method applies a neural network's self organizing algorithm forrngenerating the map display. The map display detects complex relationships among given documents, andrnreveals the relationships based on the arrangements of terms abstracted from the documents. To conduct the experiment, 330 Amharic news articles of three classes were collected from the Ethiop ianrnNews Agency. 248 of the news articles were taken as a training set and the remaining as a test set. For thernpurpose of document representation, the Vector Space Model was used. Non-content bearing terms werernremoved from the lists of terms identified from the headline and slug parts of the news articles andrnsuffix/prefix-stripping technique was applied on the remaining list . After changing terms having differentrnwriting forms in to one common form, terms with a total frequency of above 70 and below 3 were discardedrnfrom the list. Then, a matrix both for the training and test set were constructed on the remaining 142 terms .rnA normalized weight was assigned to each term in a given news article based on TF-IDF (Term Frequency InversernDocument Frequency) weighting technique and the vector matrix were prepared in appropriaternformat for the tool to be used.rnUsing Nenet (Neural Network Tool), the SOM map was trained with the 248 articles in the training set andrntested with three test sets selected from the three classes of news articles. From the distribution of thesernarticles on the map, it was observed that the map placed similar articles near each other. The resultsrnobtained from the three tests made, indicated that the clustering capability of the SOM for Amharicrndocuments is promising. Lastly, a map was constructed for the entire (330) news articles and an HTML based prototype browsingrninterface map was developed and labeled with descriptive terms that convey properties of the area. A linkrnwas also made with the actual database through the Active Server Pages created so that users can browsernon the map for relevant articles .