Searching for Communities: a Facebook Way

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval(2019)

引用 1|浏览23
暂无评分
摘要
Giving people the power to build community is central to Facebook's mission. Technically, searching for communities poses very different challenges compared to the standard IR problems. First, there is a vocabulary mismatch problem since most of the content of the communities is private. Second, the common labeling strategies based on human ratings and clicks do not work well due to limited public content available to third-party raters and users at search time. Finally, community search has a dual objective of satisfying searchers and growing the number of active communities. While A/B testing is a well known approach for assessing the former, it is an open question on how to measure progress on the latter. This talk discusses these challenges in depth and describes our solution.
更多
查看译文
关键词
causal effect, counterfactual, embeddings, explainability, privacy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要