1. Telling important party history of the New Democracy period based on historical materials
- Author
-
Hu Ding
- Subjects
knowledge graph ,entity model ,encoder ,new democratic period ,important party history ,74a30 ,Mathematics ,QA1-939 - Abstract
Due to the characteristics of multi-source heterogeneity of party history information resources, the organisation and storage of party history information resources remain in the digital stage at this stage. In order to achieve the transformation of important party history information resources in the new democratic period from digitalisation to intellectualisation, this paper collects and preprocesses the relevant information data of important party history in the new democratic period in the historical materials. The entity knowledge model in the knowledge graph is constructed by combining the characteristics of important party history with the data, encoding and processing the nodes and timestamps in the important party history by using encoders, learning its evolution characteristics, and realising the complementary processing of the time sequence of important party history. Finally, we construct a narrative system of important party history from the new democratic period based on historical materials. The study shows that there are 2015 keywords of important party history during the New Democracy period in the historical materials, and there are 36 keywords with frequency values of 3 times or more. It is also found that the system can accurately narrate important party history events in the New Democratic Period and can allow users to learn about other important party history figures or events that are closely related to them when searching for important party history-related information. This paper responds to the call for promoting the popularisation of Party history for all people, and the visual and vivid display of important Party history events through the form of knowledge mapping can improve the public’s understanding and knowledge of Party history events.
- Published
- 2024
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