Abstract: An approach is disclosed that receives a request from a requestor over a computer network, the request including a set of encrypted user data that includes interest vectors pertaining to a set of users. A homomorphic encryption processing of the encrypted user data is performed using a distance function that utilizes an encrypted lookup table. This results in a set of distance results. An encrypted distance array is then generated from the distance results. The encrypted distance array describes similarities between the users in the set of encrypted data. A set of encrypted recommendations are returned to the requestor. The recommendations returned are derived from the encrypted distance array.

Abstract: A level of classification for each piece of data of one or more pieces of data is determined. A layer of encryption for each piece of data of the one or more pieces of data is determined. A type of encryption for each piece of data of the one or more pieces of data is determined. Other mechanisms applied to each piece of data of the one or more pieces of data is determined. A first constant for the layer of encryption, a second constant for the type of encryption, a third constant for the other mechanisms applied is determined. A risk factor for each piece of data of the one or more pieces of data is determined.

Abstract: A level of classification for each piece of data of one or more pieces of data is determined. A layer of encryption for each piece of data of the one or more pieces of data is determined. A type of encryption for each piece of data of the one or more pieces of data is determined. Other mechanisms applied to each piece of data of the one or more pieces of data is determined. A first constant for the layer of encryption, a second constant for the type of encryption, a third constant for the other mechanisms applied is determined. A risk factor for each piece of data of the one or more pieces of data is determined.

Abstract: Evaluating risk of sensitive data associated with a target data set includes a computer system receiving a pattern that defines sensitive data and a selection of a data set as the target data set for evaluating. The system determines portions of the target data set from which to select sample data sets and determines, responsive to a confidence limit and sizes of the respective portions of the target data, a size of a sample data set for each respective target data set portion. The system randomly samples the target data set portions to provide sample data sets of the determined sample data set sizes and determines whether there is an occurrence of the sensitive data in each sample data set by searching for the pattern in the sample data sets. The system determines a proportion of the sample data sets that have the occurrence of the sensitive data.

Abstract: Evaluating risk of sensitive data associated with a target data set includes a computer system receiving a pattern that defines sensitive data and a selection of a data set as the target data set for evaluating. The system determines portions of the target data set from which to select sample data sets and determines, responsive to a confidence limit and sizes of the respective portions of the target data, a size of a sample data set for each respective target data set portion. The system randomly samples the target data set portions to provide sample data sets of the determined sample data set sizes and determines whether there is an occurrence of the sensitive data in each sample data set by searching for the pattern in the sample data sets. The system determines a proportion of the sample data sets that have the occurrence of the sensitive data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

Abstract: A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.