[1] Apte,C., Damerau,F., and Weiss,S., Towards
language independent automated learning of text
categorization models, In Proceedings of the
17th Annual ACM/SIGIR conference, 1994.
[2] Apte,C., Damerau,F., and Weiss,S., Text
mining with decision rules and decision trees, In
Proceedings of the Conference on Automated
Learning and Discorery, Workshop 6: Learning
from Text and the Web, 1998.
[3] Baker,L.D., Mccallum,A.K., Distributional
clustering of words for text categorization, In
Proceedings of the 21th Ann Int ACM SIGIR
Conference on Research and Development in
Information Retrieval (SIGIR'98), pages 96-103,
1998.
[4] CNN Europe Web site,
http://europe.cnn.com/, 2001.
[5] Cohen,William W., Text categorization and
relational learning, In The Twelfth International
Conference on Machine Learning (ICML'95),
Morgan Kaufmann, 1995.
[6] Cohen,William W., Singer,Yoram,
Context-sensitive learning methods for text
categorization, In SIGIR '96: Proceedings of the
19th Annual International ACM SIGIR
Conference on Research and Development in
Information Retrieval, pages 307-315, 1996.
[7] Fuhr,N., Hartmanna,S., Lustig,G.,
Schwantner,M., and Tzeras,K., Air/x - a
rule-based multistage indexing systems for large
subject fields, In 606-623, editor, Proceedings of
RIAO'91, 1991.
[8] Gore, K., Cogito Auto Sum: What less can
we say?
http://slate.msn.com/features/cogitoautosum/cogi
toautosum.asp, 2001.
[9] Joachims,Thorsten, Text Categorization with
Support Vector Machines: Learning with Many
Relevant Features, In European Conference on
Machine Learning (ECML), Berlin, pages 137-
142, 1998. Springer.
[10] Koller,D. and Sahami,M., Hierarchically
classifying documents using very few words, In
The Fourteenth International Conference on
Machine Learning (ICML'97), pages 170-178,
1997.
[11] Lam ,W. and Ho,C.Y., Using a generalized
instance set for automatic text categorization, In
Proceedings of the 21th Ann. Int. ACM SIGIR
Conference on Research and Development in
Information Retrieval (SIGIR'98), pages 81-89,
1998.
[12] Lewis,D.D. and Ringuette,M., Comparison
of two learning algorithms for text
categorization, In Proceedings of the Third
Annual Symposium on Document Analysis and
Information Retrieval (SDAIR'94), 1994.
[13] Lie, D.H., Sumatra, A system for Automatic
Summary Generation, Carp Technologies,
Hengelosestraat 174, 7521 AK Enschede, 2001.
http://www.carptechnologies.
nl/SumatraTWLT14paper/Sumatra
TWLT14.html
[14] Masand,B., Linoff, G., and Waltz,D.,
Classifying news stories using memory based
reasoning, In 15th Ann. Int. ACM SIGIR
Conference on Research and Development in
Information Retrieval (SIGIR'92), pages 59-64,
1992.
[15] McCallum, Andrew Kachites, Bow: A
toolkit for statistical language modeling, text
retrieval, classification and clustering, 1996.
http://www.cs.cmu.edu/~mccallum/bow.
[16] McCallum A. and Nigam,K., A comparison
of event models for naive bayes text
classification, In AAAI-98 Workshop on
Learning for Text Categorization, 1998.
[17] Mitchell, T.M., Machine Learning, The
McGraw-Hill Companies, Inc., 1997.
[18] Moulinier,I., Is learning bias an issue on the
text categorization problem? In Technical report,
LAFORIA-LIP6, Universite Paris VI, 1997.
Arg: A Tool For Automatic Report Generation
K. Murat KARAKAY and H. Altay GÜVENİR
1108
[19] Moulinier,I., Raskinis,G. and Ganascia,J.,
Text categorization: a symbolic approach, In
Proceedings of the Fifth Annual Symposium on
Document Analysis and Information Retrieval,
1996.
[20] Nigam, K., McCallum, A., Thrun, S. and
Mitchell, T., Learning to Classify Text from
Labeled and Unlabeled Documents, In
Proceedings of the Fifteenth National
Conference on Artificial Intelligence (AAAI-98),
pages 792-799, 1998.
[21] Neto, J. Larocca, Santos, A.D., Kaestner,
C.A.A., Freitas, A.A., Document clustering and
text summarization, Proc. 4th Int. Conf. Practical
Applications of Knowledge Discovery and Data
Mining (PADD-2000), sh=41-55, London: The
Practical Application Company, 2000.
[22] Ng,H.T., Goh,W.B., and Low,K.L., Feature
selection, perceptron learning, and a usability
case study for text categorization,In 20th Ann Int
ACM SIGIR Conference on Research and
Development in Information Retrieval
(SIGIR'97), pages 67-73,1997.
[23] Tzeras,K. and Hartman,S., Automatic
indexing based on bayesian inference networks,
In Proc 16th Ann Int ACM SIGIR Conference on
Research and Development in Information
Retrieval (SIGIR'93), pages 22-34, 1993.
[24] Wiener,E., Pedersen,J.O., and
Weigend,A.S., A neural network approach to
topic spotting, In Proceedings of the Fourth
Annual Symposium on Document Analysis and
Information Retrieval (SDAIR'95), pages 317-
332, Nevada, Las Vegas, 1995. University of
Nevada, Las Vegas.
[25] Yang ,Y., Expert network: Effective and
efficient learning from human decisions in text
categorization and retrieval, In 17th Ann Int
ACM SIGIR Conference on Research and
Development in Information Retrieval
(SIGIR'94), pages 13-22, 1994.
[26] Yang,Y., An evaluation of statistical
approaches to text categorization. Journal of
Information Retrieval, 1(1/2):67-88, 1999.
[27] Yang,Y. and Chute,C.G., An example-based
mapping method for text categorization and
retrieval, ACM Transaction on Information
Systems (TOIS), 12(3):252-277, 1994.
[28] Yang,Y. and Pedersen,J.P., A comparative
study on feature selection in text categorization,
In Jr. D. H. Fisher, editor, The Fourteenth
International Conference on Machine Learning,
pages 412-420. Morgan Kaufmann, 1997.
Thank you for copying data from http://www.arastirmax.com