Probase is an ongoing project that focuses on knowledge acquisition and knowledge serving. Our primary goal is to enable machines to understand human behavior and human communication. We do this by injecting certain general knowledge or certain common sense into computing. Knowledge in Probase is harnessed from digitized footprints of human behavior and communications. Figure 1 is a snippet of Probase, which consists of concepts (e.g. emerging markets), instances (e.g., China), attributes and values (e.g., China’s population is 1.3 billion), and relationships (e.g., emerging markets, as a concept, is closely related to newly industrialized countries), all of which are automatically derived in an unsupervised manner. But Probase is much more than a traditional ontology/taxonomy. Probase is unique because of its large scale, which can be seen in three dimensions: the concept dimension, the data dimension, and the relationship dimension.
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References in zbMATH (referenced in 4 articles )
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- Yuan, Ye; Wang, Guoren; Chen, Lei; Ning, Bo: Efficient pattern matching on big uncertain graphs (2016)
- Zang, Liang-Jun; Cao, Cong; Cao, Ya-Nan; Wu, Yu-Ming; Cao, Cun-Gen: A survey of commonsense knowledge acquisition (2013)