Building Semantic Dependency Knowledge Graph Based on HowNet

Zhu, Siqi; Li, Yang; Shao, Yanqiu; Wang, Lihui

doi:10.1007/978-3-030-38189-9_54

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…As a new knowledge representation method, a knowledge graph belongs to the category of the Semantic Web, which is used to describe various entities existing in the real world and the relationship between entities with abstract concepts (Wang et al, 2018;Zhu et al, 2019,). It can be divided into two categories, according to the coverage.…”

Section: Related Workmentioning

confidence: 99%

Research on the Construction and Application of Knowledge Graph in the Ceramic Field Based on Natural Language Processing

Nie

Huang

Peng

et al. 2023

International Journal on Semantic Web and Information Systems

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There are problems of knowledge deficiency and effective unified expression of knowledge in the process of relevant knowledge data acquired by workers in the ceramic domain. In this study, the authors designed relevant experiments to construct ceramic field knowledge graphs to solve these problems. In the experiments of named entity recognition and relationship recognition, the authors compared the performance of several models in OwnThink and ceramics field datasets. The experimental results showed that the BiLSTM-CRF model is the best for named entity recognition and the TextCNN model is the best for relationship recognition in ceramics field datasets. Therefore, the first used the BiLSTM-CRF model to complete the naming entity recognition and then combined with the TextCNN model to complete the relationship recognition to construct the ceramic field knowledge graph. Then, they applied the constructed graph to the ceramic knowledge Q&A service to provide accurate data retrieval service for ceramic domain workers.

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Section: Related Workmentioning

confidence: 99%

Research on the Construction and Application of Knowledge Graph in the Ceramic Field Based on Natural Language Processing

Nie

Huang

Peng

et al. 2023

International Journal on Semantic Web and Information Systems

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“…Other technologies that stand out in the other groups are SPARQL to query data from the KG [15,79], RDF to populate the KG with data [15,66,67], the Neo4J base to store graph data [70,81], among others.…”

Section: Knowledge Graphs and Semantic Web Technologiesmentioning

confidence: 99%

“…Additionally, the authors analyze the existing literature and compare five specific studies.•Recommendation as secondary task. In[81], the authors present KG construction and the use of open source code to make recommendations. The graph is used to provide recommendations for language units.• Recommendation as a central task.…”

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confidence: 99%

A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions

Chicaiza

Valdiviezo-Díaz

2021

Information

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In recent years, the use of recommender systems has become popular on the web. To improve recommendation performance, usage, and scalability, the research has evolved by producing several generations of recommender systems. There is much literature about it, although most proposals focus on traditional methods’ theories and applications. Recently, knowledge graph-based recommendations have attracted attention in academia and the industry because they can alleviate information sparsity and performance problems. We found only two studies that analyze the recommendation system’s role over graphs, but they focus on specific recommendation methods. This survey attempts to cover a broader analysis from a set of selected papers. In summary, the contributions of this paper are as follows: (1) we explore traditional and more recent developments of filtering methods for a recommender system, (2) we identify and analyze proposals related to knowledge graph-based recommender systems, (3) we present the most relevant contributions using an application domain, and (4) we outline future directions of research in the domain of recommender systems. As the main survey result, we found that the use of knowledge graphs for recommendations is an efficient way to leverage and connect a user’s and an item’s knowledge, thus providing more precise results for users.

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A Novel Multidimensional Comments and Co-preference Aware Recommendation Algorithm

Zhang

Song

Tang

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Building Semantic Dependency Knowledge Graph Based on HowNet

Cited by 5 publications

References 3 publications

Research on the Construction and Application of Knowledge Graph in the Ceramic Field Based on Natural Language Processing

Research on the Construction and Application of Knowledge Graph in the Ceramic Field Based on Natural Language Processing

A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions

A Novel Multidimensional Comments and Co-preference Aware Recommendation Algorithm

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