Using relational knowledge discovery to prevent securities fraud

Jennifer Neville; Özgür Şimşek; David D. Jensen; John Komoroske; Kelly Palmer; Henry Goldberg

doi:10.1145/1081870.1081922

Using relational knowledge discovery to prevent securities fraud

Jennifer Neville
, Özgür Şimşek
, David D. Jensen
, John Komoroske
, Kelly Palmer
, Henry Goldberg

Department of Computer Science

University of Massachusetts
National Association of Securities Dealers

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

83 Citations (SciVal)

Original language	English
Title of host publication	Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005
Editors	Robert Grossman, Roberto J. Bayardo, Kristin P. Bennett
Publisher	Association for Computing Machinery
Pages	449-458
Number of pages	10
DOIs	https://doi.org/10.1145/1081870.1081922
Publication status	Published - 21 Aug 2005

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10.1145/1081870.1081922

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Neville, J., Şimşek, Ö., Jensen, D. D., Komoroske, J., Palmer, K., & Goldberg, H. (2005). Using relational knowledge discovery to prevent securities fraud. In R. Grossman, R. J. Bayardo, & K. P. Bennett (Eds.), Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005 (pp. 449-458). Association for Computing Machinery. https://doi.org/10.1145/1081870.1081922

Using relational knowledge discovery to prevent securities fraud. / Neville, Jennifer; Şimşek, Özgür; Jensen, David D. et al.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005. ed. / Robert Grossman; Roberto J. Bayardo; Kristin P. Bennett. Association for Computing Machinery, 2005. p. 449-458.

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Neville, J, Şimşek, Ö, Jensen, DD, Komoroske, J, Palmer, K & Goldberg, H 2005, Using relational knowledge discovery to prevent securities fraud. in R Grossman, RJ Bayardo & KP Bennett (eds), Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005. Association for Computing Machinery, pp. 449-458. https://doi.org/10.1145/1081870.1081922

Neville J, Şimşek Ö, Jensen DD, Komoroske J, Palmer K, Goldberg H. Using relational knowledge discovery to prevent securities fraud. In Grossman R, Bayardo RJ, Bennett KP, editors, Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005. Association for Computing Machinery. 2005. p. 449-458 doi: 10.1145/1081870.1081922

Neville, Jennifer ; Şimşek, Özgür ; Jensen, David D. et al. / Using relational knowledge discovery to prevent securities fraud. Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005. editor / Robert Grossman ; Roberto J. Bayardo ; Kristin P. Bennett. Association for Computing Machinery, 2005. pp. 449-458

@inproceedings{682070837c4143339f1f78cfaeb19a2f,

title = "Using relational knowledge discovery to prevent securities fraud",

author = "Jennifer Neville and {\"O}zg{\"u}r {\c S}im{\c s}ek and Jensen, \{David D.\} and John Komoroske and Kelly Palmer and Henry Goldberg",

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T1 - Using relational knowledge discovery to prevent securities fraud

AU - Neville, Jennifer

AU - Şimşek, Özgür

AU - Jensen, David D.

AU - Komoroske, John

AU - Palmer, Kelly

AU - Goldberg, Henry

PY - 2005/8/21

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DO - 10.1145/1081870.1081922

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SP - 449

EP - 458

BT - Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005

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A2 - Bayardo, Roberto J.

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PB - Association for Computing Machinery

ER -

Using relational knowledge discovery to prevent securities fraud

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