Knowledge fusion map has a tree-like structure. It can be expressed as three tuple KFM= (T, F, KF). Among them, the T represents a domain-specific topic, such as the clustering algorithm,"K-means"; Sets F represents a collection of the T's different facets, for example, the facets of "K-means" include "overview", "feature", "algorithm step" etc. The KF represents some knowledge fragments of a T's facet.
Knowledge fusion map is mainly mined from linked data on the Semantic Web.It is organized by Resource Description Framework(RDF).At the same time, we extracted and processed some valuable data from the Wikipedia as a supplement

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