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Consumer-Oriented Multi-Party Matching Recommendation System Based Deep Learning

机译:基于消费者的多方匹配推荐系统的深度学习

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In this paper, we propose the consumer-oriented multi-party matching recommendation system based deep learning that recommends the most suitable participants to consumers when producing a work. The proposed method uses a deep learning model that takes the characteristics and constraints of the consumer as input. The deep learning model uses the Candidate Generation Model, which selects candidate candidates, and the Ranking Model, which recalculates the recommendation scores of selected candidate candidates. Therefore, a group of candidates suitable for a large candidate group is recommended.
机译:在本文中,我们提出了以消费者为导向的多方匹配推荐系统的深度学习,为生产工作时为消费者推荐最合适的参与者。该方法使用深度学习模型,该模型将消费者的特征和约束作为输入。深度学习模型使用选择候选候选人的候选生成模型,以及排序模型,该排名模型重新计算所选候选人的建议评分。因此,建议使用适合大候选群的一组候选者。

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