References
Liu W Q, Liu J, Wang M, et al. Faceted fusion of RDF data. Inf Fusion, 2015, 23: 16–24
Huang W D, Khoury R, Dawborn T, et al. WeBeVis: analyzing user web behavior through visual metaphors. Sci China Inf Sci, 2013, 56: 052106
Bajaj R, Sharma V. Smart education with artificial intelligence based determination of learning styles. Procedia Comput Sci, 2018, 132: 834–842
Hodge G. Systems of knowledge organization for digital libraries: beyond traditional authority files. Council on Library and Information Resources Pub91, 2000. http://www.clir.org/pubs/reports/pub91/pub91.pdf
Bollacker K, Evans C, Paritosh P, et al. Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of ACM SIGMOD International Conference on Management of Data, 2008. 1247–1250
Wu W T, Li H S, Wang H X, et al. Probase: a probabilistic taxonomy for text understanding. In: Proceedings of ACM SIGMOD International Conference on Management of Data, 2012. 481–492
Dong X L, Gabrilovich E, Heitz G, et al. Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014. 601–610
Liu J, Jiang L, Wu Z H, et al. Mining learning-dependency between knowledge units from text. VLDB J, 2011, 20: 335–345
Wu B, Wei B F, Liu J, et al. Facet annotation by extending CNN with a matching strategy. Neural Comput, 2018, 30: 1647–1672
Acknowledgements
This work was supported by National Key Research and Development Program of China (Grant No. 2018YFB1004500), National Natural Science Foundation of China (Grant Nos. 61532015, 61532004, 61672419, 61672418), Innovative Research Group of National Natural Science Foundation of China (Grant No. 61721002), Innovation Research Team of Ministry of Education (Grant No. IRT_17R86), and Project of China Knowledge Centre for Engineering Science and Technology.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zheng, Q., Liu, J., Zeng, H. et al. Knowledge forest: a novel model to organize knowledge fragments. Sci. China Inf. Sci. 64, 179103 (2021). https://doi.org/10.1007/s11432-018-9940-0
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-018-9940-0