Abstract: Identifying one or more patterns of content consumption across multiple entities and determining an engagement action for a user of an entity based on the patterns may include receiving information associated with content, cross-industry user data associated with consumption of the content, and a given organization user data associated with consumption of the content. A first set of consumption profile vectors associated with the given organization and one or more second set of consumption profile vectors associated respectively with one or more cross-industry organizations may be generated. Information associated with a target user in the given organization may be received. A customized learning plan for the target user in the given organization may be generated based on the first set of consumption profile vectors, the one or more second set of consumption profile vectors, and the information associated with the target user.

Abstract: Selecting candidates from a set of candidates by receiving a set of input parameters about a single aspect of the candidates and applying multiple scoring methods to those input parameters to compute a candidate score via each scoring method. A subset of zero or more candidates is then selected from the set of candidates by applying one or more selection criteria to the set of scores. There is not necessarily a value for every input parameter of every candidate.

Abstract: A method of managing access to a physical mailing address using a virtual mailing address is presented. The method includes: setting up a proxy system as a server, assigning, by a server, a virtual mailing address identifier to natural or juristic person that registers with the server; linking, by the server, a physical mailing address entered by the user to the virtual mailing address identifier to generate the virtual mailing address; and enabling, by the server, a second natural person to manually access the physical mailing address when the server determines that the second user has permission to access the virtual mailing address; enabling, by the server, an institute or business (juristic person) to access the physical mailing address automatically using an Application programming interface (API) through a computer system when the server determines that the second user has permission to access the virtual mailing address.

Abstract: A user trajectory graph may be constructed based on spatio-temporal data and mobility pattern extracted from trajectory graph. Users may be clustered into groups, wherein the users in a same group posses similar feature values in the mobility pattern, and the users in different groups have different feature values, to identify personas and location sets. A distribution model may be constructed that models user timing and location preference, wherein an outcome indicates a preference for a particular time bin on a particular day for a particular location.

Abstract: Identifying one or more patterns of content consumption across multiple entities and determining an engagement action for a user of an entity based on the patterns may include receiving information associated with content, cross-industry user data associated with consumption of the content, and a given organization user data associated with consumption of the content. A first set of consumption profile vectors associated with the given organization and one or more second set of consumption profile vectors associated respectively with one or more cross-industry organizations may be generated. Information associated with a target user in the given organization may be received. A customized learning plan for the target user in the given organization may be generated based on the first set of consumption profile vectors, the one or more second set of consumption profile vectors, and the information associated with the target user.

Abstract: Ultra-wide bandwidth (UWB) transmission is a promising technology for indoor localization due to its fine delay resolution and obstacle-penetration capabilities. However, the presence of walls and other obstacles present a significant challenge in terms of localization, as they result in positively biased distance estimates. Measurement campaigns with FCC-compliant UWB radios can quantify effects of non-line-of-sight (NLOS) propagation. Features of waveforms measured during a campaign can be extracted for use in distinguishing between NLOS and line-of-sight situations in embodiments of the present invention. Embodiments further include classification and regression methods based on machine learning that improve the localization performance while relying solely on the received signal. Applications for systems employing an example embodiment of the invention include indoor or outdoor search and recovery with high accuracy and low cost.

Abstract: A method of managing access to a physical mailing address using a virtual mailing address is presented. The method includes: setting up a proxy system as a server, assigning, by a server, a virtual mailing address identifier to natural or juristic person that registers with the server; linking, by the server, a physical mailing address entered by the user to the virtual mailing address identifier to generate the virtual mailing address; and enabling, by the server, a second natural person to manually access the physical mailing address when the server determines that the second user has permission to access the virtual mailing address; enabling, by the server, an institute or business (juristic person) to access the physical mailing address automatically using an Application programming interface (API) through a computer system when the server determines that the second user has permission to access the virtual mailing address.

Abstract: Enterprise learning system may receive as input learning goals for a learner. Learning goals may also be specified by job-roles. The system may output course-sequence recommendations, sequence-associations to learning goals and learning-goal recommendations. A semantic analysis may automatically relate learning-goals to learning assets and job-roles. Computational semantic relation-finding may leverage available knowledge-bases. A sequence-recommendation recommends course or learning asset sequences to the learner based on historical usage, the learner's current and/or desired job-roles and learning goals.

Abstract: Selecting candidates from a set of candidates by receiving a set of input parameters about a single aspect of the candidates and applying multiple scoring methods to those input parameters to compute a candidate score via each scoring method. A subset of zero or more candidates is then selected from the set of candidates by applying one or more selection criteria to the set of scores. There is not necessarily a value for every input parameter of every candidate.

Abstract: A tool for computational generation of organizational mentoring relationships. The tool determines a mentor pool and a mentee pool based, at least in part, on per-person domain metric data for each person in a general pool. The tool determines a plurality of per-metric ranked mentor lists for each of the one or more mentees in the mentee pool. The tool determines a per-mentee fused rank list for each of the one or more mentees in the mentee pool. The tool determines, based, at least in part, on the per-mentee fused rank list for each of the one or more mentees in the mentee pool, one or more cross-organizational mentorship assignments. The tool establishes, based, at least in part, on the one or more cross-organizational mentorship assignments, at least one mentor-mentee relationship for each of the one or more mentees in the mentee pool.

Abstract: Techniques for quantifying the quality of trend lines. A method includes defining a collection of reference data sets derived from multiple historical projects in a similar subject area as the target project, defining one or more indicators of data set applicability to a target project estimation, said defining based on multiple characteristics of the target project, evaluating applicability of each of the reference data sets based on the one or more indicators, and identifying one or more of the reference data sets as applicable for use in the target project estimation.

Abstract: Ultra-wide bandwidth (UWB) transmission is a promising technology for indoor localization due to its fine delay resolution and obstacle-penetration capabilities. However, the presence of walls and other obstacles present a significant challenge in terms of localization, as they result in positively biased distance estimates. Measurement campaigns with FCC-compliant UWB radios can quantify effects of non-line-of-sight (NLOS) propagation. Features of waveforms measured during a campaign can be extracted for use in distinguishing between NLOS and line-of-sight situations in embodiments of the present invention. Embodiments further include classification and regression methods based on machine learning that improve the localization performance while relying solely on the received signal. Applications for systems employing an example embodiment of the invention include indoor or outdoor search and recovery with high accuracy and low cost.

Abstract: Ultra-wide bandwidth (UWB) transmission is a promising technology for indoor localization due to its fine delay resolution and obstacle-penetration capabilities. However, the presence of walls and other obstacles present a significant challenge in terms of localization, as they result in positively biased distance estimates. Measurement campaigns with FCC-compliant UWB radios can quantify effects of non-line-of-sight (NLOS) propagation. Features of waveforms measured during a campaign can be extracted for use in distinguishing between NLOS and line-of-sight situations in embodiments of the present invention. Embodiments further include classification and regression methods based on machine learning that improve the localization performance while relying solely on the received signal. Applications for systems employing an example embodiment of the invention include indoor or outdoor search and recovery with high accuracy and low cost.

Abstract: A method for estimating a risk associated with a project includes preparing a plurality of data models, where each of the plurality of data models examines a different dimension of the project, classifying each of the plurality of data models to produce a plurality of prediction models, where each of the plurality of prediction models is defined by a plurality of quality metrics, and where the plurality of quality metrics includes a preliminary estimate of the risk and a measure of confidence in the preliminary estimate, and computing a refined estimate of the risk based on a quality of the plurality of quality metrics.

Abstract: A method for estimating a risk associated with a project includes preparing a plurality of data models, where each of the plurality of data models examines a different dimension of the project, classifying each of the plurality of data models to produce a plurality of prediction models, where each of the plurality of prediction models is defined by a plurality of quality metrics, and where the plurality of quality metrics includes a preliminary estimate of the risk and a measure of confidence in the preliminary estimate, and computing a refined estimate of the risk based on a quality of the plurality of quality metrics.

Abstract: Ranking a plurality of objects includes obtaining an initial set of data relating to the objects, generating an initial set of estimates based on the initial set of data, wherein the initial set of estimates includes, for each of the objects, an initial estimated change in performance and an initial estimated likelihood of decline in the performance, incrementally and dynamically refining the initial set of estimates in accordance with a new set of data from new data sources and relating to the objects to produce a refined set of estimates, wherein the refined set of estimates includes, for each of the objects, a refined estimated change in performance and a refined estimated likelihood of decline in the performance, without modifying or replacing a system used to generate the initial set of estimates, and generating a list that ranks the objects according to the refined set of estimates.

Abstract: Techniques, apparatus and articles of manufacture for quantifying the quality of trend lines. A method includes defining a collection of reference data sets derived from multiple historical projects in a similar subject area as the target project, defining one or more indicators of data set applicability to a target project estimation, said defining based on multiple characteristics of the target project, evaluating applicability of each of the reference data sets based on the one or more indicators, and identifying one or more of the reference data sets as applicable for use in the target project estimation.

Abstract: Apparatus and articles of manufacture for quantifying the quality of trend lines include defining a collection of reference data sets derived from multiple historical projects in a similar subject area as the target project, defining one or more indicators of data set applicability to a target project estimation, said defining based on multiple characteristics of the target project, evaluating applicability of each of the reference data sets based on the one or more indicators, and identifying one or more of the reference data sets as applicable for use in the target project estimation.

Abstract: The reward or return a company receives in a particular country relative to the risk the company takes in that country is assessed. The relative risk of the particular country compared to selected groups of countries, for example groups including countries having emerging or developing economies and groups including countries having developed economies. The relative profitability of the particular country in relation to the profitability of such groups of countries is further considered in the assessment. Other return components are also considered to allow risk adjusted decisions.

Abstract: A plan to incentivize performance is obtained based on objective and subjective metrics. A first step encompasses understanding the effect of actions on each objective metric on future service provider performance. A subset of objective metrics is obtained via regression analysis. For the subset identified in the first step, a set of clusters is identified in the multi-dimensional space of objective metrics. For each cluster, actions based on service provider performance relating to subjective metrics are effected. Expert guidance based on macroeconomic factors are further considered.