Recommending the World's Knowledge: Application of Recommender Systems at Quora

Lei Yang, X. Amatriain
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引用次数: 15

Abstract

At Quora, our mission is to share and grow the world's knowledge. Recommender systems are at the core of this mission: we need to recommend the most important questions to people most likely to write great answers, and recommend the best answers to people interested in reading them. Driven by the above mission statement, we have a variety of interesting and challenging recommendation problems and a large, rich data set that we can work with to build novel solutions for them. In this talk, we will describe several of these recommendation problems and present our approaches solving them.
推荐世界知识:Quora推荐系统的应用
在Quora,我们的使命是分享和发展世界知识。推荐系统是这项任务的核心:我们需要向最有可能写出好答案的人推荐最重要的问题,并向有兴趣阅读这些问题的人推荐最佳答案。在上述使命声明的推动下,我们有了各种有趣且具有挑战性的推荐问题,以及一个庞大而丰富的数据集,我们可以利用这些数据集为它们构建新颖的解决方案。在这次演讲中,我们将描述其中的几个推荐问题,并介绍我们解决这些问题的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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