Abstract: Implementations include providing, by the PKG platform, an initial knowledge graph based on user-specific data associated with a user, and a domain-specific knowledge graph, receiving, by the PKG platform, data representative of at least one answer provided from the user to a respective question, providing, by the PKG platform, an expanded knowledge graph based on the initial knowledge graph, the expanded knowledge graph including one or more nodes and respective edges based on the data, generating, by the PKG platform, a weighted knowledge graph based a groundtruth knowledge graph, and a targeted knowledge graph, the groundtruth knowledge graph including one or more true answers, and the targeted knowledge graph including the at least one answer provided from the user, and generating, by the PKG platform, the hyper-personalized knowledge graph (hpKG) based on the weighted knowledge graph, the hpKG being unique to the user within a domain.

Abstract: A skill acquisition platform may receive input identifying a target role for a user, may identify users from the plurality of users that have worked in the target role, may identify, based on a similarity metric, a subset of the users that have worked in the target role and have similar career trajectories to the user, may cluster vectors of the user and vectors of the subset of the users that have worked in the target role to generate a plurality of skill groups, may generate a directed network graph that represents links between the plurality of skill groups, may identify one or more paths between a first skill group associated with the user and a second skill group associated with the target role, and may automatically generate a descriptive analysis of the one or more paths.

Abstract: In some implementations, a device may receive a set of role skills data that identifies one or more role skills associated with a role, a set of worker skills data that identifies one or more worker skills associated with a worker, and a set of skill proximity data that identifies one or more proximity values. The device may generate a weighted directed graph comprising a network of a plurality of nodes and a plurality of edges. The device may determine a fitness of a worker for a role based at least in part on performing a comparison of a maximum network flow with a threshold. The device may perform an action based at least in part on determining the fitness of the worker for the role.

Abstract: Implementations include providing, by the PKG platform, an initial knowledge graph based on user-specific data associated with a user, and a domain-specific knowledge graph, receiving, by the PKG platform, data representative of at least one answer provided from the user to a respective question, providing, by the PKG platform, an expanded knowledge graph based on the initial knowledge graph, the expanded knowledge graph including one or more nodes and respective edges based on the data, generating, by the PKG platform, a weighted knowledge graph based a groundtruth knowledge graph, and a targeted knowledge graph, the groundtruth knowledge graph including one or more true answers, and the targeted knowledge graph including the at least one answer provided from the user, and generating, by the PKG platform, the hyper-personalized knowledge graph (hpKG) based on the weighted knowledge graph, the hpKG being unique to the user within a domain.

Abstract: Implementations include providing, by the PKG platform, an initial knowledge graph based on user-specific data associated with a user, and a domain-specific knowledge graph, receiving, by the PKG platform, data representative of at least one answer provided from the user to a respective question, providing, by the PKG platform, an expanded knowledge graph based on the initial knowledge graph, the expanded knowledge graph including one or more nodes and respective edges based on the data, generating, by the PKG platform, a weighted knowledge graph based a groundtruth knowledge graph, and a targeted knowledge graph, the groundtruth knowledge graph including one or more true answers, and the targeted knowledge graph including the at least one answer provided from the user, and generating, by the PKG platform, the hyper-personalized knowledge graph (hpKG) based on the weighted knowledge graph, the hpKG being unique to the user within a domain.

Abstract: A skill acquisition platform may receive input identifying a target role for a user, may identify users from the plurality of users that have worked in the target role, may identify, based on a similarity metric, a subset of the users that have worked in the target role and have similar career trajectories to the user, may cluster vectors of the user and vectors of the subset of the users that have worked in the target role to generate a plurality of skill groups, may generate a directed network graph that represents links between the plurality of skill groups, may identify one or more paths between a first skill group associated with the user and a second skill group associated with the target role, and may automatically generate a descriptive analysis of the one or more paths.

Abstract: Implementations include providing, by the PKG platform, an initial knowledge graph based on user-specific data associated with a user, and a domain-specific knowledge graph, receiving, by the PKG platform, data representative of at least one answer provided from the user to a respective question, providing, by the PKG platform, an expanded knowledge graph based on the initial knowledge graph, the expanded knowledge graph including one or more nodes and respective edges based on the data, generating, by the PKG platform, a weighted knowledge graph based a groundtruth knowledge graph, and a targeted knowledge graph, the groundtruth knowledge graph including one or more true answers, and the targeted knowledge graph including the at least one answer provided from the user, and generating, by the PKG platform, the hyper-personalized knowledge graph (hpKG) based on the weighted knowledge graph, the hpKG being unique to the user within a domain.