Integration of Fragmented Knowledge Based on Knowledge Graph

DOI

10.2991/978-94-6463-502-7_57How to use a DOI?

Keywords

Knowledge graph; PageRank innovation algorithm; Fragmented knowledge; Knowledge integration

Abstract

With the widespread adoption of user-generated content (UGC) platforms, the influx of fragmented knowledge makes it increasingly complex to integrate and utilize this knowledge across platforms. This study proposes an innovative approach based on knowledge graph and PageRank algorithm to effectively integrate fragmented knowledge in different UGC platforms. In this paper, fragmented knowledge from different platforms is collected. After data preprocessing, PageRank innovation algorithm is used to calculate the importance score of each knowledge node, and the relevance and importance of nodes are taken as the basis of integration, and it is organically organized into a unified knowledge graph. Nodes in the graph represent knowledge elements on different UGC platforms, while edges represent the relationships between them, forming a hierarchical integrated knowledge graph. Experiments show that this method can not only significantly improve the quality of integrated knowledge, but also effectively solve the problem of information fragmentation among different UGC platforms. This research provides an innovative solution for cross-platform fragmented knowledge integration, so as to help learners make better use of fragmented knowledge to improve learning effect, provide better learning resources and guidance for educators and learners. It is expected to be widely used in the field of knowledge management and integration.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiaojun Chen
AU  - Liu Yuan
PY  - 2024
DA  - 2024/08/31
TI  - Integration of Fragmented Knowledge Based on Knowledge Graph
BT  - Proceedings of the 2024 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024）
PB  - Atlantis Press
SP  - 547
EP  - 555
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-502-7_57
DO  - 10.2991/978-94-6463-502-7_57
ID  - Chen2024
ER  -