SPaRKLE: Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarning

doi:doi:10.57702/y62s0xfg

SPaRKLE: Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarning

SPaRKLE is a hybrid method that combines symbolic and mathematical methodologies while leveraging Partial Completness Assumption (PCA) heuristics to capture implicit information and enrich Knowledge Graphs (KGs). The combination of symbolic and numerical strategies offers a comprehensive approach to KG enrichment that capitalizes on the strengths of both paradigms. This technique has the potential to provide more extensive, accurate, interpretable, and flexible knowledge representations, thereby improving the usefulness and efficacy of KGs across several domains.

BibTex:

@dataset{Disha_Purohit_and_Yashrajsinh_Chudasama_and_Ariam_Rivas_and_Maria-Esther_Vidal_2024,
    abstract = {SPaRKLE is a hybrid method that combines symbolic and mathematical methodologies while leveraging Partial Completness Assumption (PCA) heuristics to capture implicit information and enrich Knowledge Graphs (KGs). The combination of symbolic and numerical strategies offers a comprehensive approach to KG enrichment that capitalizes on the strengths of both paradigms. This technique has the potential to provide more extensive, accurate, interpretable, and flexible knowledge representations, thereby improving the usefulness and efficacy of KGs across several domains.},
    author = {Disha Purohit and Yashrajsinh Chudasama and Ariam Rivas and Maria-Esther Vidal},
    doi = {10.57702/y62s0xfg},
    institution = {TIB},
    keyword = {'Benchmark'},
    month = {jul},
    publisher = {TIB},
    title = {SPaRKLE: Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarning},
    url = {https://service.tib.eu/ldmservice/dataset/sparkle-symbolic-capturing-of-knowledge-for-knowledge-graph-enrichment-with-learning},
    year = {2024}
}