本文選題：網(wǎng)絡(luò)電視直播 + 實時推薦��； 參考：《微電子學(xué)與計算機(jī)》2016年12期

【摘要】：提出一種基于語義和用戶偏好的網(wǎng)絡(luò)電視直播實時推薦方法.該方法首先基于用戶的歷史記錄構(gòu)建用戶偏好模型,然后使用基于詞向量的語義相似度計算方法,分別計算待推薦節(jié)目和用戶記錄或待推薦節(jié)目和用戶當(dāng)前觀看節(jié)目間的相似度,再結(jié)合該相似度和用戶偏好求取用戶對待推薦節(jié)目的虛擬興趣,最后選出虛擬興趣較高的一組節(jié)目作為對用戶的實時推薦.實驗結(jié)果表明,此方法的命中率在實時預(yù)測推薦的場景下較對比方法提高了10%以上,且在實時節(jié)目推薦的場景下有更好的推薦效果.
[Abstract]:A real-time broadcast real-time recommendation method based on semantic and user preferences is proposed. This method first constructs user preference model based on user history records, and then uses semantic similarity calculation method based on word vectors to calculate respectively the recommended programs and user records or the recommended programs and the user's current viewing programs. The similarity degree is combined with the similarity degree and the user preference to obtain the user's virtual interest in the recommended program. Finally, a group of programs with higher virtual interest is selected as the real-time recommendation for the user. The experimental results show that the hit rate of this method is 10% higher than the comparison method under the real-time prediction recommendation scene, and is recommended in the real-time program. There is a better recommendation in the scene.
【作者單位】： 中國科學(xué)技術(shù)大學(xué)信息科學(xué)技術(shù)學(xué)院;上海文廣互動電視有限公司;
【基金】：中科院先導(dǎo)課題(XDA060112030)
【分類號】：TP391.3

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