Hotness prediction of scientific topics based on a bibliographic knowledge graph

Huo, Chaoguang; Ma, Shutian; Liu, Xiaozhong

doi:10.1016/j.ipm.2022.102980

Cited by 17 publications

(2 citation statements)

References 49 publications

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“…Generally, a lower perplexity indicates a better number of topics and a better topic clustering effect (Zhang and Dong, 2020). As the number of topics increases, the perplexity will keep decreasing (Huo et al, 2021). However, the excessive number of topics will cause excessive dispersion of topics, resulting in a poor topic clustering effect.…”

Section: Data Processing Of the Citing Papers' Topicsmentioning

confidence: 99%

The impact of library and information science knowledge from the perspective of external citations

Guo

2022

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Purpose This paper aims to explore the characteristics of knowledge diffusion in library and information science (LIS) to reveal the impact of knowledge in LIS on other disciplines and the disciplinary status of LIS. Design/methodology/approach Taking the 573 highly cited papers (HCP) of LIS during the years 2000–2019 in Web of Science and 85,638 papers citing them from non-LIS disciplines as the analysis object, this paper analysed the disciplines to which the citing papers belonged regarding the Biglan model, and the topics and their characteristics of the citing disciplines using latent Dirichlet allocation topic clustering. Findings The results showed that the knowledge in LIS was exported to multiple disciplines and topics. (1) Citations from other disciplines were overall increasing, and the main citing disciplines, mainly from applied science disciplines, were medicine, computer science, management, economics, education, sociology, psychology, journalism and communication, earth science, engineering, biology, political science, chemistry and agronomy. However, those disciplines had fewer citations to LIS during for the years from 2000 to 2004, with rapid growth in the next three time periods. (2) The citing papers had various topics and showed an increasing trend in quantity. Moreover, topics of different disciplines from 2000 to 2019 had various characteristics. Originality/value From the perspective of discipline and topic, this study analyses papers citing the HCP of LIS from non-LIS disciplines, revealing the impact of knowledge in LIS on other disciplines.

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Section: Data Processing Of the Citing Papers' Topicsmentioning

confidence: 99%

The impact of library and information science knowledge from the perspective of external citations

Guo

2022

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“…As a new paradigm of knowledge processing, the development of knowledge graphs brings new possibilities for UAV knowledge management [3]. Objectively, knowledge graphs have more powerful data synthesis governance capabilities, and on a large scale, multi-source and different forms of UAV knowledge data can be deeply mined and represent the semantic relation and knowledge systems the graph contains.…”

Section: Introductionmentioning

confidence: 99%

Research on the Intelligent Construction of UAV Knowledge Graph Based on Attentive Semantic Representation

Fan

Sun

et al. 2023

Drones

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Accurate target recognition of unmanned aerial vehicles (UAVs) in the intelligent warfare mode relies on a highly standardized UAV knowledge base, and thus it is crucial to construct a knowledge graph suitable for UAV multi-source information fusion. However, due to the lack of domain knowledge and the cumbersome and inefficient construction techniques, the intelligent construction approaches of knowledge graphs for UAVs are relatively backward. To this end, this paper proposes a framework for the construction and application of a standardized knowledge graph from large-scale UAV unstructured data. First, UAV concept classes and relations are defined to form specialized ontology, and UAV knowledge extraction triples are labeled. Then, a two-stage knowledge extraction model based on relational attention-based contextual semantic representation (UASR) is designed based on the characteristics of the UAV knowledge extraction corpus. The contextual semantic representation is then applied to the downstream task as a key feature through the Multilayer Perceptron (MLP) attention method, while the relation attention mechanism-based approach is used to calculate the relational-aware contextual representation in the subject–object entity extraction stage. Extensive experiments were carried out on the final annotated dataset, and the model F1 score reached 70.23%. Based on this, visual presentation is achieved based on the UAV knowledge graph, which lays the foundation for the back-end application of the UAV knowledge graph intelligent construction technology.

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Efficacy of Knowledge Graphs to Systematize Primitive Research Methodology

Jyothi,

Subbulakshmi,

Elngar

2024

Lecture Notes in Networks and Systems

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Hotness prediction of scientific topics based on a bibliographic knowledge graph

Cited by 17 publications

References 49 publications

The impact of library and information science knowledge from the perspective of external citations

The impact of library and information science knowledge from the perspective of external citations

Research on the Intelligent Construction of UAV Knowledge Graph Based on Attentive Semantic Representation

Efficacy of Knowledge Graphs to Systematize Primitive Research Methodology

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