Patents Assigned to Kronos Talent Management Inc.
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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: 7555441Abstract: A variety of technologies are applied to conceptualization of job candidate information. For example, concepts can be extracted from a job candidate's resume via an ontology. Concepts can be arranged hierarchically within the ontology, and parent concepts can be extracted. Concepts relating to job skills, job title, management, and the like can be extracted. A set of concepts can be represented as a point in n-dimensional concept space. Thus, candidates and desired candidate criteria can be represented in the concept space. Those candidates closest to the desired candidate criteria in the concept space can be designated as matches for the desired candidate criteria.Type: GrantFiled: October 10, 2003Date of Patent: June 30, 2009Assignee: Kronos Talent Management Inc.Inventors: Daniel Nicholas Crow, Visnu Ted Pitiyanuvath
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Patent number: 7472097Abstract: A plurality of neural networks or other models can be used in employee selection technologies. A hiring recommendation can be based at least on processing performed by a plurality of neural networks. For example, parallel or series processing by neural networks can be performed. A neural network can be coupled to one or more other neural networks. A binary or other n-ary output can be generated by one or more of the neural networks. In a series arrangement, candidates can be processed sequentially in multiple stages, and those surviving the stages are recommended for hire.Type: GrantFiled: March 20, 2006Date of Patent: December 30, 2008Assignee: Kronos Talent Management Inc.Inventors: David J. Scarborough, Bjorn Chambless, Anne Thissen-Roe
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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