Learning of Knowledge Graphs with Entity Descriptions

Abstract

The representing learning makes specialty of knowledge graph and it indicates the difference between different entities. The knowledge graph representing with the low-dimensional space. In fact, most of the method usually concern of description of entity which is hard for existing strategies to take benefit of. Here, we recommend a new representing learning method with knowledge graphs that uses entity description. We evaluate our method on two tasks like knowledge graph and entity classification. Experimental effects on actual-world datasets show that our version plays higher than different baseline fashions, especially under the zero-short setting, which indicate that our technique for novel the entity description.

Authors and Affiliations

Yacouba Conde , Zhoulianying ,

Keywords

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  • EP ID EP705442
  • DOI 10.47191/ijmra/v5-i2-07
  • Views 64
  • Downloads 0

How To Cite

Yacouba Conde, Zhoulianying, (2022). Learning of Knowledge Graphs with Entity Descriptions. International Journal of Multidisciplinary Research and Analysis, 5(02), -. https://europub.co.uk/articles/-A-705442