Abstract: The present disclosure relates to a method and system for recommending optimal ergonomic position for a user of a computing device by a recommendation system. The recommendation system receives user data from one or more data sources and extracts a profile of the user from a repository based on the user data. The recommendation system identifies one or more critical areas of the user, where each of the critical areas are associated with a plurality of pre-defined position parameters and also monitor the plurality of pre-defined position parameters of the user to determine corresponding values. The recommendation system compare the values of the plurality of pre-defined position parameters with predefined values of the pre-defined position parameters and identify deviations in one or more of the plurality of pre-defined position parameters based on the comparison and provide recommendations for correcting the deviations from the pre-defined position parameters to the user.

Abstract: According to an exemplary embodiment, a method for generating an enterprise user group is provided. The method may include receiving a set of attributes for an enterprise network user; receiving one or more enterprise group member identification rules including a similarity distance threshold and a set of target attributes; calculating, using a hardware processor, a similarity assessment score based on the set of target attributes and the set of attributes; and determining, using the hardware processor, whether the enterprise network user is an enterprise group member based on the similarity assessment score and the similarity distance threshold.

Abstract: The present disclosure relates to a method and system for recommending optimal ergonomic position for a user of a computing device by a recommendation system. The recommendation system receives user data from one or more data sources and extracts a profile of the user from a repository based on the user data. The recommendation system identifies one or more critical areas of the user, where each of the critical areas are associated with a plurality of pre-defined position parameters and also monitor the plurality of pre-defined position parameters of the user to determine corresponding values. The recommendation system compare the values of the plurality of pre-defined position parameters with predefined values of the pre-defined position parameters and identify deviations in one or more of the plurality of pre-defined position parameters based on the comparison and provide recommendations for correcting the deviations from the pre-defined position parameters to the user.

Abstract: According to an exemplary embodiment, a method for generating an enterprise user group is provided. The method may include receiving a set of attributes for an enterprise network user; receiving one or more enterprise group member identification rules including a similarity distance threshold and a set of target attributes; calculating, using a hardware processor, a similarity assessment score based on the set of target attributes and the set of attributes; and determining, using the hardware processor, whether the enterprise network user is an enterprise group member based on the similarity assessment score and the similarity distance threshold.