2025年系统集成新课程同步导学练测高中英语必修第二册
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C
Artificial intelligence (AI) still can't see the future, but a new algorithm (算法) may come close: using nothing but written movie summaries, AI can consistently tell which films will play well or awfully to critics and audiences. If the model can be further improved, it could one day help producers predict whether a movie will be a failure at the box office, before it's even made.
To test several AI models, researchers used plot summaries of 42,306 movies from all over the world. The models broke the summaries by sentence and used something called sentiment (情感) analysis to analyze each one. Sentences considered “positive”, such as “Thor loves his hammer”, would receive a rating (等级) closer to positive one. And sentences that were considered “negative”, like “Thor gets in a fight” would be rated closer to negative one.
Generally, successful movies such as 1951's Alice in Wonderland—which scored 80% on the movie-rating website—have frequent waves in sentiment; unsuccessful ones, such as 2009's The Limits of Control, vary less. It's not important whether the films begin or end happily, the researchers say. What's important is that the sentiments change frequently.
The sentiment ratings in each summary were then simplified (简化) into a single score to reflect how often the sentiments changed. The researchers tested three different methods of arriving at a final score. All three could predict fairly accurately whether a movie would be unpopular, and one method worked especially well for guessing which thrillers and comedies reviewers would hate.
The methods were not as efficient at guessing which movies would succeed, but they still predicted the results more accurately than random (随机的) chance. In the future, the researchers say their methods could be bettered to predict the amount a movie could earn at the box office and help producers decide which movies to invest (投资) in. The system's fair judgment might give an advantage to less well-known writers, the researchers add. It could also potentially save the public from having to sit through films like Jaws: The Revenge, which online critics and audiences alike rate terrible.
28. How can AI help predict the future of movies?
A. By testing plot models.
B. By using sentiment analysis.
C. By writing summaries.
D. By consulting critics and audiences.
29. What is the key to a successful movie according to the researchers?
A. A happy ending.
B. Famous movie stars.
C. A well-known producer.
D. Frequent sentiment changes.
30. What benefit will the methods possibly bring?
A. Increasing box office earnings.
B. Assessing a movie's quality accurately.
C. Providing written summaries for critics.
D. Helping producers invest wisely.
31. What's the researchers' attitude to the model?
A. Doubtful.
B. Cautious.
C. Optimistic.
D. Unclear.
Artificial intelligence (AI) still can't see the future, but a new algorithm (算法) may come close: using nothing but written movie summaries, AI can consistently tell which films will play well or awfully to critics and audiences. If the model can be further improved, it could one day help producers predict whether a movie will be a failure at the box office, before it's even made.
To test several AI models, researchers used plot summaries of 42,306 movies from all over the world. The models broke the summaries by sentence and used something called sentiment (情感) analysis to analyze each one. Sentences considered “positive”, such as “Thor loves his hammer”, would receive a rating (等级) closer to positive one. And sentences that were considered “negative”, like “Thor gets in a fight” would be rated closer to negative one.
Generally, successful movies such as 1951's Alice in Wonderland—which scored 80% on the movie-rating website—have frequent waves in sentiment; unsuccessful ones, such as 2009's The Limits of Control, vary less. It's not important whether the films begin or end happily, the researchers say. What's important is that the sentiments change frequently.
The sentiment ratings in each summary were then simplified (简化) into a single score to reflect how often the sentiments changed. The researchers tested three different methods of arriving at a final score. All three could predict fairly accurately whether a movie would be unpopular, and one method worked especially well for guessing which thrillers and comedies reviewers would hate.
The methods were not as efficient at guessing which movies would succeed, but they still predicted the results more accurately than random (随机的) chance. In the future, the researchers say their methods could be bettered to predict the amount a movie could earn at the box office and help producers decide which movies to invest (投资) in. The system's fair judgment might give an advantage to less well-known writers, the researchers add. It could also potentially save the public from having to sit through films like Jaws: The Revenge, which online critics and audiences alike rate terrible.
28. How can AI help predict the future of movies?
A. By testing plot models.
B. By using sentiment analysis.
C. By writing summaries.
D. By consulting critics and audiences.
29. What is the key to a successful movie according to the researchers?
A. A happy ending.
B. Famous movie stars.
C. A well-known producer.
D. Frequent sentiment changes.
30. What benefit will the methods possibly bring?
A. Increasing box office earnings.
B. Assessing a movie's quality accurately.
C. Providing written summaries for critics.
D. Helping producers invest wisely.
31. What's the researchers' attitude to the model?
A. Doubtful.
B. Cautious.
C. Optimistic.
D. Unclear.
答案:
28. B 29. D 30. D 31. C
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