預測冷啟動的新影片熱門度 | |
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學年 | 106 |
學期 | 2 |
出版(發表)日期 | 2018-06-01 |
作品名稱 | 預測冷啟動的新影片熱門度 |
作品名稱(其他語言) | Predicting the popularity of new video for cold start problem |
著者 | 張嘉玲 |
單位 | |
出版者 | |
著錄名稱、卷期、頁數 | |
摘要 | Predicting video popularity is an important task involved in managing video-sharing sites. Although many previous studies have investigated this problem, a weakness common to these studies is that their predictions rely on video access data from the past. In other words, they cannot predict the popularity of newly uploaded videos. To handle this cold start problem, this study focused on building prediction models that use only the data available at the time when a video is initially uploaded. Through supervised learning methods, this study employed prediction models to predict the popularity of videos. To further improve the overall accuracy of the prediction, we used an ensemble model to integrate these classification results to obtain the most accurate prediction. The empirical evaluation indicated that the models are effective for predicting the popularity of a video and that our model can solve the cold start problem of video popularity prediction. |
關鍵字 | data mining;popularity prediction;cold start;YouTube |
語言 | en |
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相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120439 ) |
SDGS | 優質教育,尊嚴就業與經濟發展,產業創新與基礎設施 |