A user-adaptive indexing model of structured documents

In this paper we present an indexing model of multimedia documents having a hierarchical structure; this model allows users to generate personal document representations. The documents are organised into logical (thematic) sections where the index terms play a distinct role as descriptors of the documents´ information contents. The indexed archive can be heterogeneous, i.e. it may contain documents with distinct logical structures. The proposed indexing model is adaptive to the user, who can indicate in the retrieval phase the preferred sections of documents, i.e. those which they estimate to bear the most interesting information, and can linguistically quantify the number of sections which determine the global potential interest of the documents. The adaptation is carried out by a flexible query language for expressing the aforementioned soft selection conditions on the structured documents.