| 摘要 |
A media content item is evaluated for its "sentiment states." That is, segments of the content item are determined to be, for example, "happy," "exciting," "sad," "funny," and the like. A "sentiment map" is created that delimits segments of the content item and contains the sentiment-state keywords associated with the segments. Some maps include an amplitude for each assigned sentiment keyword and a confidence value for the segment delimitation and for each keyword. As an exemplary use of the sentiment map, an advertisement broker matches the sentiments of his advertisement offerings with segments of a content item in order to place appropriate advertisements at times when they would be most favorably received. In another example, a recommender system recommends to a user a content item whose sentiment map compares favorably to that of a content item already enjoyed by the user.
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