Abstract: A method and system provide the ability to determine matching subjects for features provided in a stimulus. Subject information is pre-processed by receiving input (a feature type definition and a subject set) and building BitSets across all subjects in the subject set. The stimulus is received and includes stimulus features. For each feature type in the stimulus features, all feature type BitSets from the subject set that match are assembled. An evaluation BitSet is built by combining the assembled feature type BitSets. Matching subjects that match the stimulus are determined based on the evaluation BitSet.

Abstract: A method and system provide the ability to determine matching subjects for features provided in a stimulus. Subject information is pre-processed by receiving input (a feature type definition and a subject set) and building BitSets across all subjects in the subject set. The stimulus is received and includes stimulus features. For each feature type in the stimulus features, all feature type BitSets from the subject set that match are assembled. An evaluation BitSet is built by combining the assembled feature type BitSets. Matching subjects that match the stimulus are determined based on the evaluation BitSet.

Abstract: A method, apparatus, system, and computer program product display information about selected content in a social network. Multiple icons representative of content are displayed. Via input from a user, an item of the content is selected by selecting one of the multiple icons. In response to the selecting, a tooltip is displayed. The tooltip includes relevant information about the selected item and affinity data that provides a probability of similar interests between the user and the selected item.

Abstract: A method, apparatus, system, and computer program product provide an affinity between a first entity and a second entity on a social network. First affinity data for a first entity is determined. The first affinity data is first behavioral data and first categorical data. Second affinity data for the second entity is determined. The second affinity data is second behavioral data and second categorical data. The first affinity data is compared to the second affinity data resulting in an affinity score. The affinity score identifies a probability of similar interests between the first entity and the second entity based on behavioral similarities between the first behavioral data and the second behavioral data, and categorical similarities between the first categorical data and the second categorical data. The affinity score is then provided to the first entity.

Abstract: A method, apparatus, system, and computer program product display information about selected content in a social network. Multiple icons representative of content are displayed. Via input from a user, an item of the content is selected by selecting one of the multiple icons. In response to the selecting, a tooltip is displayed. The tooltip includes relevant information about the selected item and affinity data that provides a probability of similar interests between the user and the selected item.