| 摘要 |
<p>A user's context history is analyzed to build a personality model describing the user's personality and interests. The personality model includes a plurality of metrics indicating the user's position on a plurality of personality dimensions, such as desire for novelty, tendency for extravagance, willingness to travel, love of the outdoors, preference for physical activity, and desire for solitude. A customized recommendation agent is then built based on the personality model, which selects a recommendation from a corpus to present to the user based on an affinity between the user's personality and the selected recommendation.</p> |
