Abstract: At least one processor identifies dependency relationships among libraries in a repository of libraries. Using the dependency relationships among libraries, at least one machine learning model can be created that predicts with a confidence value a dependency between a given library and a target library. An L layer tree-like graph can be created, using the dependency relationships among libraries and an application package. L can be configurable. Versions of the libraries to use can be determined by running the at least one machine learning model for each pair of nodes having a dependency relationship in the L layer tree-like graph, the at least one machine learning model identifying the dependency relationship with a confidence value, where pairs of nodes having largest confidence values are selected as the versions of the libraries to use in the application package.

Abstract: The present disclosure relates to privacy protection in a search process. According to a method, a target emotion vector is extracted from a search interaction, the target emotion vector representing emotional information in the search interaction. Respective emotion distances between the target emotion vector and respective emotion vectors associated with a plurality of text clusters are determined. The plurality of text clusters is clustered from a dictionary of text elements. A first number of text clusters are selected from the plurality of text clusters based on the determined respective emotion distances. The first number of text clusters have emotion distances larger than at least one unselected text cluster among the plurality of text clusters. A plurality of confused search interactions are constructed for the search interaction based on the first number of text clusters, and the plurality of confused search interactions are performed.

Abstract: An approach is provided in which the approach loads a machine learning model and a set of test case statistical data into a user system. The set of test case statistical data is based on a set of test cases corresponding to the machine learning model and includes a plurality of input parameter sets and a corresponding set of output quality measurements. The approach compares user data on the user system against the set of test case statistical data and identifies one of the plurality of input parameter sets to optimize the machine learning model based on the set of output quality measurements. The approach generates an optimized machine learning model using the machine learning model and the identified input parameter set at the user system.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.

Abstract: Embodiments of the present disclosure relate to adaptive RFID communication. A tag device includes a storage configured to store content that is executable by a proxy device associated with a reader device. The tag device includes a communication component configured to transmit the content to the reader device, the content, when executed by the proxy device, causing an action associated with the tag device to be performed.