JUCS - Journal of Universal Computer Science 3(8): 1007-1021, doi: 10.3217/jucs-003-08-1007
A Framework for Filtering News and Managing Distributed Data
Gianni Amati‡, Daniela D Aloisi‡, Vittorio Giannini‡, Flavio Ubaldini§‡ Fondazione Ugo Bordoni, Italy§ Università di Roma 'La Sapienza', Italy
Corresponding author: Gianni Amati ( gba@fub.it ) © Gianni Amati, Daniela Aloisi, Vittorio Giannini, Flavio Ubaldini. This article is freely available under the J.UCS Open Content License. Citation:
Amati G, Aloisi DD, Giannini V, Ubaldini F (1997) A Framework for Filtering News and Managing Distributed Data. JUCS - Journal of Universal Computer Science 3(8): 1007-1021. https://doi.org/10.3217/jucs-003-08-1007 |  |
Abstract
With the development and diffusion of the Internet worldwide connection, a large amount of information is available to the users. Methods of information filtering and fetching are then required. This paper presents two approaches. The first concerns the information filtering system ProFile based on an adaptation of the generalized probabilistic model of information retrieval. ProFile filters the netnews and uses a scale of 11 predefined values of relevance. ProFile allows the user to update on--line the profile and to check the discrepancy between the assessment and the prediction of relevance of the system. The second concerns ABIS, an intelligent agent for supporting users in filtering data from distributed and heterogeneous archives and repositories. ABIS minimizes user s effort in selecting the huge amount of available documents. The filtering engine memorizes both user preferences and past situations. ABIS compares documents with the past situations and finds the similarity scores on the basis of a memory-based reasoning approach.
Keywords
information filtering, information gathering, internet, agent-based systems, probabilistic model, memory-based reasoning