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Md Saiful Islam and Fei Liu
In the realm of artificial intelligence, knowledge graphs have become an effective area of research. Relationships between entities are depicted through a structural framework in knowledge graphs. In this paper, we propose to build a domain-specific medi...
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Xin Tian and Yuan Meng
The judicious configuration of predicates is a crucial but often overlooked aspect in the field of knowledge graphs. While previous research has primarily focused on the precision of triples in assessing knowledge graph quality, the rationality of predic...
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Vasilis Bouras, Dimitris Spiliotopoulos, Dionisis Margaris, Costas Vassilakis, Konstantinos Kotis, Angeliki Antoniou, George Lepouras, Manolis Wallace and Vassilis Poulopoulos
Digital assistants?such as chatbots?facilitate the interaction between persons and machines and are increasingly used in web pages of enterprises and organizations. This paper presents a methodology for the creation of chatbots that offer access to museu...
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Wenxiao Li, Hongyan Mei, Yutian Li, Jiayao Yu, Xing Zhang, Xiaorong Xue and Jiahao Wang
Due to the fast retrieval speed and low storage cost, cross-modal hashing has become the primary method for cross-modal retrieval. Since the emergence of deep cross-modal hashing methods, cross-modal retrieval significantly improved. However, the existin...
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Miao Tian, Xinxin Hu, Jiakai Huang, Kai Ma, Haiyan Li, Shuai Zheng, Liufeng Tao and Qinjun Qiu
The growing proliferation of geographic information presents a substantial challenge to the traditional framework of a geographic information analysis and service. The dynamic integration and representation of geographic knowledge, such as triples, with ...
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Huansha Wang, Qinrang Liu, Ruiyang Huang and Jianpeng Zhang
Multi-modal entity alignment refers to identifying equivalent entities between two different multi-modal knowledge graphs that consist of multi-modal information such as structural triples and descriptive images. Most previous multi-modal entity alignmen...
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Botao Zhang, Yong Feng, Lin Fu, Jinguang Gu and Fangfang Xu
Entity and relation linking are the core tasks in knowledge base question answering (KBQA). They connect natural language questions with triples in the knowledge base. In most studies, researchers perform these two tasks independently, which ignores the ...
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Xiaochun Sun, Chenmou Wu and Shuqun Yang
With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in com...
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Hasna Boumechaal and Zizette Boufaida
Querying Linked Data is one of the most important issues for the semantic web community today because it requires the user to understand the structure and vocabularies used in various data sources. Furthermore, users must be familiar with the syntax of q...
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Ning Yu, Jianyi Liu and Yu Shi
With the development of information extraction technology, a variety of entity-relation extraction paradigms have been formed. However, approaches guided by these existing paradigms suffer from insufficient information fusion and too coarse extraction gr...
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