Link-Based Shaping of Hypermedia Documents Assisted by a Neural Agent

The paper proposes a neural agent that performs self-organizing classification to assist in searching and contributing to webs of documents and in the process of document reuse. By applying the Kohonen self-organizing feature map (SOFM) algorithm to patterns of influence links among documents it is possible to originate clusters of documents that help infer the aspects that such documents implicitly share. The approach complements search techniques based on semantic indexes. The resulting classification is sensitive to the multiple aspects of a document that may belong to multiple classes with a varying degree and allows for treating effectively items that typically have a limited life span, either because they are means to the collaborative production of a more complex item, or because they belong to fast evolving domains. The method has been implemented by Lotus Notes Domino Web server for a case-based application in the domain of information systems design. © Springer Pub. Co.