Knowledge revision for document understanding

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1325, Issue , 1997, Pages 619-628

  Esposito, Floriana ^a   Malerba, Donato ^a   Semeraro, Giovanni ^a   Ferilli, Stefano ^a  

^a UNIVERSITY OF BARI   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL LIBRARIES; INTELLIGENT SYSTEMS; SEMANTICS;

AUTOMATED PROCESSING; DOCUMENT UNDERSTANDING; INCREMENTAL LEARNING; KNOWLEDGE MAINTENANCE; KNOWLEDGE REVISION; REAL-WORLD LEARNING; REFINEMENT OPERATORS; SEMANTIC INDEXING;

LEARNING SYSTEMS;

EID: 84947718382     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63614-5_60     Document Type: Conference Paper

References (13)

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2. Claric K. L., Negation as failure in Logic and Databases, H. Gallaire and J. Minker (eds.), Plenum Press, New Yoik, 293-321, 1978.
3. Esposito, P., Malerba, D., and Semeraro, G., Multistrategy Learning for Document Recognition, Applied Artificial intelligence: An International Journal, Vol. 8, No. 1, 33-84, 1994.
4. Esposito F., Laterza A., Malerba D. and Semeraro G., Locally Finite, Proper and Complete Operatorsfor Refining Datalog Programs, in Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence 1097, Z. W. Ras and M. Michalewicz (Eds.), Springer, 468-478, 1996.
5. Esposito F., Maleiba D. and Semeraro G., From Machine Perception to Machine Learning: generating models of visual objects, in Machine Learning and Perception, 139-148, G. Tascini, F. Esposito, V. Roberto and P. Zingaretti (Eds.), Singapore: World Scientific, 1996.
6. Esposito F., Malerba D., Semeraro G., Fanizzi N., and Ferilli, S., Adding Intelligence to Digital Libraries: IDL, IJCAI-97 Workshop on AI in Digital Libraries-Moving From Chaos to (More) Order, 1997.
7. Grant, J., & Subrahmanian, V. S., Reasoning in Inconsistent Knowledge Bases, IEEE Transactions on Knowledge and Data Engineering, Vol. 7, N. 1, 177-189, 1995.
8. Helft, N., Inductive Generalization: A Logical Framework, in Progress in Machine Learning, I. Bratko & N. Lavrac (Eds.), Sigma Press, Wilmslow, 149-157, 1987.
9. Lloyd, J. W., Foundations of Logic Programming, Second Edition, Springer-Verlag, New York, 1987.
10. Malerba, D., Semeraro, G., and Esposito, F., A multistrategy approach to learning multiple dependent concepts. In Machine Learning andStatistics: The Interface, C. Taylor andR. Nakhaeizadeh (Eds.), Wiley, London, pp. 87-106, 1997.
11. Oikin M. and Drogin R., Vital Statistics, McGraw-Hill, 1990.
12. Semeraro G., Esposito F. andMalerba D., Ideal Refinement of Datalog Programs, in Logic Program Synthesis and Transfoimation, Lecture Notes in Computer Science 1048, M. Proietti (Ed.), Springer, 1996.
13. van der Laag P. R. J. and Nienhuys-Cheng S.-H., A Note on Ideal Refinement Operators in Inductive Logic Programming, ILP-94, S. Wrobel (Ed.), GMD-studien Nr. 237, 247-260, 1994.