Knowledge Discovery from Texts with Conceptual Graphs and FCA
نویسندگان
چکیده
Building conceptual lattices from conceptual graphs looks as natural way in Formal Concept Analysis but still is not discovered at length. If conceptual graphs are acquired from natural language texts then they contain specific material for knowledge discovery. Conceptual graphs serve as semantic models of text sentences and the data source for concept lattice. With the use of concept lattice it is possible to extract information which can be treated as facts. Facts can be extracted by using navigation in the lattice and interpretation its concepts and hierarchical links between them. Experimental investigation of this knowledge discovery technique is performed on the annotated textual corpus consisted of descriptions of biotopes of bacteria.
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تاریخ انتشار 2017