Abstract: A method of machine learning that teaches a computer to determine likelihood that a medical journal article is classified as high value for an intended system. In some embodiments, the method includes procuring, in a medical articles database on the computer, a training set including medical articles recommended by subject matter experts associated with medical journals that have published the medical articles. The method can also include identifying, by a feature extraction controller of the computer, first features in the medical articles via a remote annotation service and a remote article information service. The method can also include identifying, by intended system services electronically available to the intended system, second features in the medical articles. The method can also include reducing, by the feature extraction controller, the first and second features to form a set of relevant features.

Abstract: A method of machine learning that teaches a computer to determine likelihood that a medical journal article is classified as high value for an intended system. In some embodiments, the method includes procuring, in a medical articles database on the computer, a training set including medical articles recommended by subject matter experts associated with medical journals that have published the medical articles. The method can also include identifying, by a feature extraction controller of the computer, first features in the medical articles via a remote annotation service and a remote article information service. The method can also include identifying, by intended system services electronically available to the intended system, second features in the medical articles. The method can also include reducing, by the feature extraction controller, the first and second features to form a set of relevant features.

Abstract: In an approach to content selection, one or more computer processors receive a first query from a user. The one or more computer processors retrieve a first response for the first query. The one or more computer processors determine whether the first response exceeds a threshold for a policy for content usage associated with the first response, wherein the policy for content usage specifies one or more restrictions for usage of a content asset. In response to determining the first response exceeds the threshold for the policy for content usage, the one or more computer processors select a first subset of the first response to meet the threshold for the policy for content usage. The one or more computer processors send the first subset of the first response to the user.

Abstract: A method of machine learning that teaches a computer to determine likelihood that a medical journal article is classified as high value for an intended system. In some embodiments, the method includes procuring, in a medical articles database on the computer, a training set including medical articles recommended by subject matter experts associated with medical journals that have published the medical articles. The method can also include identifying, by a feature extraction controller of the computer, first features in the medical articles via a remote annotation service and a remote article information service. The method can also include identifying, by intended system services electronically available to the intended system, second features in the medical articles. The method can also include reducing, by the feature extraction controller, the first and second features to form a set of relevant features.

Abstract: A method of machine learning that teaches a computer to determine likelihood that a medical journal article is classified as high value for an intended system. In some embodiments, the method includes procuring, in a medical articles database on the computer, a training set including medical articles recommended by subject matter experts associated with medical journals that have published the medical articles. The method can also include identifying, by a feature extraction controller of the computer, first features in the medical articles via a remote annotation service and a remote article information service. The method can also include identifying, by intended system services electronically available to the intended system, second features in the medical articles. The method can also include reducing, by the feature extraction controller, the first and second features to form a set of relevant features.

Abstract: In an approach to content selection, one or more computer processors receive a first query from a user. The one or more computer processors retrieve a first response for the first query. The one or more computer processors determine whether the first response exceeds a threshold for a policy for content usage associated with the first response, wherein the policy for content usage specifies one or more restrictions for usage of a content asset. In response to determining the first response exceeds the threshold for the policy for content usage, the one or more computer processors select a first subset of the first response to meet the threshold for the policy for content usage. The one or more computer processors send the first subset of the first response to the user.