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Fourth International Conference Document Analysis and Recognition (ICDAR'97)
Information Capture and Semantic Indexing of Digital Libraries through Machine Learning Techniques
Ulm, GERMANY
August 18-August 20
ISBN: 0-8186-7898-4
Floriana Esposito, Universita' degli Studi di Bari
Donato Malerba, Universita' degli Studi di Bari
Giovanni Semeraro, Universita' degli Studi di Bari
Cesare Daniele Antifora, Universita' degli Studi di Bari
Gioacchino de Gennaro, Universita' degli Studi di Bari
This paper presents a prototypical digital library service. It integrates machine learning tools and techniques in order to make effective, efficient and economically feasible the process of capturing the information that should be stored and indexed by content in the digital library. In fact, information capture is one of the main bottlenecks when building a digital library, since it involves complex pattern recognition problems, such as document analysis, classification and understanding. Experimental results show that learning systems can solve effectively and efficiently all these problems.
Citation:
Floriana Esposito, Donato Malerba, Giovanni Semeraro, Cesare Daniele Antifora, Gioacchino de Gennaro, "Information Capture and Semantic Indexing of Digital Libraries through Machine Learning Techniques," icdar, pp.722, Fourth International Conference Document Analysis and Recognition (ICDAR'97), 1997
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