Electronic employee selection systems and methods

Data processing: artificial intelligence – Knowledge processing system – Creation or modification

Reexamination Certificate

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C706S014000, C706S012000

Reexamination Certificate

active

07080057

ABSTRACT:
An automated employee selection system can use a variety of techniques to provide information for assisting in selection of employees. For example, pre-hire and post-hire information can be collected electronically and used to build an artificial-intelligence based model. The model can then be used to predict a desired job performance criterion (e.g., tenure, number of accidents, sales level, or the like) for new applicants. A wide variety of features can be supported, such as electronic reporting. Pre-hire information identified as ineffective can be removed from a collected pre-hire information. For example, ineffective questions can be identified and removed from a job application. New items can be added and their effectiveness tested. As a result, a system can exhibit adaptive learning and maintain or increase effectiveness even under changing conditions.

REFERENCES:
patent: 5059127 (1991-10-01), Lewis et al.
patent: 5117353 (1992-05-01), Stipanovich et al.
patent: 5164897 (1992-11-01), Clark et al.
patent: 5170362 (1992-12-01), Greenberg et al.
patent: 5197004 (1993-03-01), Sobotka et al.
patent: 5326270 (1994-07-01), Ostby et al.
patent: 5416694 (1995-05-01), Parrish et al.
patent: 5461699 (1995-10-01), Arbabi et al.
patent: 5490097 (1996-02-01), Swenson et al.
patent: 5551880 (1996-09-01), Bonnstetter et al.
patent: 5565316 (1996-10-01), Kershaw
patent: 5592375 (1997-01-01), Salmon et al.
patent: 5618182 (1997-04-01), Thomas
patent: 5671409 (1997-09-01), Fatseas et al.
patent: 5722418 (1998-03-01), Bro
patent: 5727128 (1998-03-01), Morrison
patent: 5774883 (1998-06-01), Andersen et al.
patent: 5788504 (1998-08-01), Rice et al.
patent: 5827070 (1998-10-01), Kershaw et al.
patent: 5832497 (1998-11-01), Taylor
patent: 5885087 (1999-03-01), Thomas
patent: 5978768 (1999-11-01), McGovern et al.
patent: 5980096 (1999-11-01), Thalhammer-Reyero
patent: 6035295 (2000-03-01), Klein
patent: 6056556 (2000-05-01), Braun et al.
patent: 6070143 (2000-05-01), Barney et al.
patent: 6086382 (2000-07-01), Thomas
patent: 6115646 (2000-09-01), Fiszman et al.
patent: 6126448 (2000-10-01), Ho et al.
patent: 6144838 (2000-11-01), Sheehan
patent: 6189029 (2001-02-01), Feurst
patent: 6213780 (2001-04-01), Ho et al.
patent: 6259890 (2001-07-01), Driscoll et al.
patent: 6266659 (2001-07-01), Nadkami
patent: 6289340 (2001-09-01), Puram et al.
patent: 6311164 (2001-10-01), Ogden
patent: 6338628 (2002-01-01), Smith
patent: 6341267 (2002-01-01), Taub
patent: 6370510 (2002-04-01), McGovern et al.
patent: 6385620 (2002-05-01), Kurzius et al.
patent: 6442370 (2002-08-01), Driscoll et al.
patent: 6466914 (2002-10-01), Mitsuoka et al.
patent: 6484010 (2002-11-01), Sheehan
patent: 6493723 (2002-12-01), Busche
patent: 6513042 (2003-01-01), Anderson et al.
patent: 6514079 (2003-02-01), McMenimen et al.
patent: 6514084 (2003-02-01), Thomas
patent: 6524109 (2003-02-01), Lacy et al.
patent: 6567784 (2003-05-01), Bukow
patent: 6611822 (2003-08-01), Beams et al.
patent: 6618734 (2003-09-01), Williams et al.
patent: 6640216 (2003-10-01), Loofbourrow et al.
patent: 6681098 (2004-01-01), Pfenninger et al.
patent: 6691122 (2004-02-01), Witte et al.
patent: 6735570 (2004-05-01), Lacy et al.
patent: 6769066 (2004-07-01), Botros et al.
patent: 6873964 (2005-03-01), Williams et al.
patent: 2001/0011280 (2001-08-01), Gilbert et al.
patent: 2001/0031457 (2001-10-01), Pfenninger et al.
patent: 2001/0042000 (2001-11-01), Defoor, Jr.
patent: 2002/0019940 (2002-02-01), Matteson et al.
patent: 2002/0042786 (2002-04-01), Scarborough et al.
patent: 2002/0055866 (2002-05-01), Dewar
patent: 2002/0128892 (2002-09-01), Farenden
patent: 2002/0128893 (2002-09-01), Farenden
patent: 2002/0128894 (2002-09-01), Farenden
patent: 2002/0198766 (2002-12-01), Magrino et al.
patent: 2003/0037032 (2003-02-01), Neece et al.
patent: 2003/0101091 (2003-05-01), Levin et al.
patent: 2003/0191680 (2003-10-01), Dewar
patent: 2003/0195786 (2003-10-01), Dewar
patent: 2003/0200136 (2003-10-01), Dewar
patent: WO 99/17242 (1999-04-01), None
Ajay K. Aggarwal, Selection of Surgical Residents: A Neural Network Approach, 2000, Cybernetics and Systems, 417-430.
Garson,Neural Networks An Introductory Guide for Social Scientists, SAGE Publications, pp. 1-194, 1998.
“NeuralWorks Professional II/PLUS,” http://www.neuralware.com/products—pro2.jsp, pp. 1-3, Jul. 28, 2001.
“Statistica Neural Networks,” http://www.statsoft.com/stat—nn.html, pp. 1-11, Jul. 28, 2001.
Scarborough, “Tutorial on the Use of Neural Network Models for Personal Selection,”Decision Sciences Institute Southwest Region Theory and Applications Proceedings 27thAnnual Conference, pp. 151-153, Mar. 6-9, 1996.
Marshall et al., “Neural Network Modeling of Risk Assessment in Child Protective Services,”Psychological Methods, vol. 5, No. 1, pp. 102-124, 2000.
Aggarwal et al., “Selection of Surgical Residents: A Neural Network Approach,”Cybernetics and Systems: An International Journal, vol. 31, pp. 417-430, 2000.
Collins et al., “An Application of the Theory of Neural Computation to the Prediction of Workplace Behavior: An Illustration and Assessment of Network Analysis,”Personnel Psychology, vol. 46, pp. 503-524, 1993.
Mitchell, “How to Reduce the High Cost of Turnover,” Lawson Software, pp. 1-11, Jul. 12, 2001, or before.
Page et al., “Panel: Strategic Directions in Simulation Research,”Proceedings of the 1999 Winter Simulation Conference, pp. 1509-1520, 1999.
Mengel et al., “Using a Neural Network to Predict Student Responses,”ACM, pp. 669-676, 1992.
Pentland et al., “Modeling and Prediction of Human Behavior,”M.I.T. Media Lab Perceptual Computing Technical Report, No. 433, pp. 1-7, 1999.
Langley et al., “Applications of Machine Learning and Rule Induction,”Communications of the ACM, vol. 38, No. 11, pp. 55-64, Nov. 1995.
“XpertRule® Miner, The Complete Data Mining Solution,” http://www.attar.com/pages/info—xm/htm., pp. 1-5, Mar. 23, 2001.
“The Wide Scale Deployment of Active Data Mining Solutions,” http://www.attar.com/tutor/deploy.htm, pp. 1-7, Mar. 23, 2001.
“A Hybrid GA-Heuristic Search Strategy,” http://www.attar.com/pages/dev—gap.htm, pp. 1-6, Mar. 23, 2001.
Doyle et al., “Strategic Directions in Artificial Intelligence,”ACM Computing Surveys, vol. 28, No. 4, pp. 653-670, Dec. 1996.
Callaghan, “Personalization on the Fly- SaffronOne, FrontMind Tap Advanced Technologies to Predict User Behavior, Make Recommendations,”eWeek, p. 52, Oct. 23, 2000.
Hensher et al., “A Comparison of the Predictive Potential of Artificial Neural Networks and Nested Logit Models for Commuter Mode Choice,”Transportation Research Part E: Logistic and Transportation Review, vol. 36, No. 3, pp. 155-172 (abstract only), Sep. 2000.
Kahney, “KnowledgeMiner 2 Digs Out More Info,”MacWEEK, vol. 11, No. 40, pp. 23-24, Oct. 20, 1997.
Rosen, “Mining Database Treasures,”Computing Canada, vol. 22, No. 20, pp. 42-43, Sep. 26, 1996.
McLeod et al., “Predicting Credit Risk: A Neural Network Approach,”Journal of Retail Banking, vol. 15, No. 3, pp. 37-40, Fall 1993.
“SaffronOne's Unique Product Features,” http://www.saffrontech.com/pages/products/features.html, pp. 1-2, Mar. 22, 2001.
Herschel et al., “CKOS and Knowledge Management: Exploring Opportunities for Using Information Exchange Protocols,”ACM, pp. 42-50, 1999.
Hapgood, “Embedded Logic,” http://www2.cio.com/archive/050100—revisit—content.html, pp. 1-3, Mar. 23, 2001.
Brachman et al., “Mining Business Databases,”Communications of the ACM, vol. 39, No. 11, pp. 42-48, Nov. 1996.
Jordan et al., “Neural Networks,”The Computer Science and Engineering Handbook, Tucker (ed.), pp. 536-556, 1996.
Scarborough, “An Evaluation of Backpropagation Neural Network Modeling as an Alternative Methodology for C

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