Validating and Extending Semantic Knowledge Bases using Video Games with a Purpose
Validating and Extending Semantic Knowledge Bases using Video Games with a Purpose
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有目的地使用视频游戏来验证和扩展语义知识库
DOI：
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发表时间：
2014
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通讯作者：
Roberto Navigli
中科院分区：
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作者：
Daniele Vannella;David Jurgens;Daniele Scarfini;D. Toscani;Roberto Navigli
大型知识库是自然语言处理中的重要资产。通常，这样的资源是通过自动合并互补资源来构建的，例如WordNet和维基百科。然而，即使在使用众包等方法时，手动验证这些资源的成本也是昂贵的。我们提出了一种使用有目的的视频游戏来验证和扩展知识库的经济有效的方法。开发了两款视频游戏来验证概念-概念和概念-图像关系。在与众包相比的实验中，我们发现，即使玩家没有得到补偿，基于视频游戏的验证也会一致地产生更高质量的注释。
Large-scale knowledge bases are important assets in NLP. Frequently, such resources are constructed through automatic mergers of complementary resources, such as WordNet and Wikipedia. However, manually validating these resources is pro-hibitively expensive, even when using methods such as crowdsourcing. We pro-pose a cost-effective method of validating and extending knowledge bases using video games with a purpose. Two video games were created to validate concept-concept and concept-image relations. In experiments comparing with crowdsourcing, we show that video game-based validation consistently leads to higher-quality annotations, even when players are not compensated.