Amato, Flora (2009) Methodologies and Techniques for Semantic Management of Documents in Dematerialization Processes. [Tesi di dottorato] (Unpublished)
Preview |
PDF
amato.pdf Download (7MB) | Preview |
Item Type: | Tesi di dottorato |
---|---|
Resource language: | English |
Title: | Methodologies and Techniques for Semantic Management of Documents in Dematerialization Processes |
Creators: | Creators Email Amato, Flora flora.amato@unina.it |
Date: | 30 November 2009 |
Number of Pages: | 175 |
Institution: | Università degli Studi di Napoli Federico II |
Department: | Informatica e sistemistica |
Scuola di dottorato: | Ingegneria dell'informazione |
Dottorato: | Ingegneria informatica ed automatica |
Ciclo di dottorato: | 22 |
Coordinatore del Corso di dottorato: | nome email Garofalo, Francesco franco.garofalo@unina.it |
Tutor: | nome email Mazzeo, Antonino mazzeo@unina.it |
Date: | 30 November 2009 |
Number of Pages: | 175 |
Keywords: | Semantic Document Management, Information Retrieval, Knowledge Management |
Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni |
Date Deposited: | 24 May 2010 08:31 |
Last Modified: | 05 Nov 2014 10:54 |
URI: | http://www.fedoa.unina.it/id/eprint/3888 |
DOI: | 10.6092/UNINA/FEDOA/3888 |
Collection description
Knowledge management has become a challenging issue for almost all the e-Government based applications. One of the main issues for E-Government activities is to manage the great amount of available data efficiently. The presence of a huge amount of information, in fact, is typical of bureaucratic processes, like the ones pertaining to public administrations. Such information is often recorded on paper or on different digital files and its management is very expensive, both in terms of space used for storing and in terms of time spent in searching for the documents of interest. Furthermore, the manual management of these documents is absolutely not error-free. In order to efficiently access the information embedded in very large document repositories, techniques for semantic document management are required. They ensure a large and intense process of dematerialization and aim at eliminating or at least reducing, the amount of paper documents. E-Government based applications need proper data models for information content characterization, in order to automatically transformunstructured (or sometimes semi-structured) documents into formally structured records, suitable for machine processing. Furthermore a way for presenting information contained in documents, depending on access policies and available technologies has to be provided. Finally different kinds of media elements, contained in digital documents, have to be managed. Indeed, nowadays, almost all the novel bureaucratic processes are characterized by both text and multimedia data (e. g. audio, still images, sometimes videos), which need to be properly handled, stored and distributed. In this thesis, we present a novel model of digital documents for improving the dematerialization effectiveness, that constitutes the starting point for an information system able to manage documents streams efficiently. This model takes into account E-Government applications needs like as the respect of provisions in force and the adaptability to evolving technologies. At the best of our knowledge, the proposed model is one of the first attempts to give a single and unified characterization for the management of multimedia documents, pertaining to a bureaucratic domain as the E-Government one, on which a system of semantic procedures are defined for the transformation of the non structured documents (pertaining to specialized domain) into structured data. Furthermore, architecture for the management of the document whole life cycle has been proposed, which provides advanced functionalities for semantic processing, such as giving formal structure to document informative content, information extraction, semantic retrieval, indexing, storage, presentation, together with long-term preservation.
Downloads
Downloads per month over past year
Actions (login required)
View Item |