在LinkedIn内容搜索引擎中引入语义能力
Introducing Semantic Capability in LinkedIn's Content Search Engine
AI总结：
本文针对用户查询日益复杂化的趋势，介绍了LinkedIn新型内容搜索引擎的语义能力设计，并展示了其对搜索指标的影响。
摘要：
过去，用户向搜索引擎发出的大多数查询都是简短而简单的，基于关键词的搜索引擎能够很好地回答这类查询。然而，用户现在逐渐养成了发出冗长且复杂的自然语言查询的习惯。回答此类查询需要搜索引擎演进以具备语义能力。在本文中，我们介绍了LinkedIn新型内容搜索引擎的设计，该引擎具备语义能力，并展示了其对各项指标的影响。
英文摘要：
In the past, most search queries issued to a search engine were short and simple. A keyword based search engine was able to answer such queries quite well. However, members are now developing the habit of issuing long and complex natural language queries. Answering such queries requires evolution of a search engine to have semantic capability. In this paper we present the design of LinkedIn's new content search engine with semantic capability, and its impact on metrics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
