Patents by Inventor Deme M. Clainos
Deme M. Clainos has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 8265977Abstract: 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.Type: GrantFiled: February 17, 2011Date of Patent: September 11, 2012Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20120215710Abstract: 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.Type: ApplicationFiled: April 27, 2012Publication date: August 23, 2012Applicant: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20120078804Abstract: 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.Type: ApplicationFiled: September 23, 2011Publication date: March 29, 2012Applicant: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Patent number: 8046251Abstract: 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.Type: GrantFiled: October 8, 2004Date of Patent: October 25, 2011Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20110145161Abstract: 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.Type: ApplicationFiled: February 17, 2011Publication date: June 16, 2011Applicant: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, Joel R. Smith
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Publication number: 20100287110Abstract: 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.Type: ApplicationFiled: July 22, 2010Publication date: November 11, 2010Applicant: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20100287111Abstract: 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.Type: ApplicationFiled: July 22, 2010Publication date: November 11, 2010Applicant: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Patent number: 7562059Abstract: 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.Type: GrantFiled: August 11, 2004Date of Patent: July 14, 2009Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Patent number: 7558767Abstract: 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.Type: GrantFiled: August 2, 2001Date of Patent: July 7, 2009Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Patent number: 7310626Abstract: 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.Type: GrantFiled: January 24, 2005Date of Patent: December 18, 2007Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Patent number: 7080057Abstract: 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.Type: GrantFiled: August 2, 2001Date of Patent: July 18, 2006Assignee: Unicru, Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20020046199Abstract: 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.Type: ApplicationFiled: August 2, 2001Publication date: April 18, 2002Applicant: Unicru, Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith
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Publication number: 20020042786Abstract: 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.Type: ApplicationFiled: August 2, 2001Publication date: April 11, 2002Applicant: Unicru, Inc.Inventors: David J. Scarborough, Bjorn Chambless, Richard W. Becker, Thomas F. Check, Deme M. Clainos, Maxwell W. Eng, Joel R. Levy, Adam N. Mertz, George E. Paajanen, David R. Smith, John R. Smith