Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health cond...Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health conditions and it is commonly used alongside conventional medical treatments.With the development of artificial intelligence(AI)technology,new possibilities for improving the efficacy and precision of acupuncture have emerged.This study explored the combination of traditional acupuncture and AI technology from three perspectives:acupuncture diagnosis,prescription,and treatment evaluation.The study aimed to provide cutting-edge direction and theoretical assistance for the development of an acupuncture robot.展开更多
Biography is a direct and extensive way to know the representation of well known peoples, however, for common people, there is poor knowledge for them to be recognized. In recent years, information extraction （IE） t...Biography is a direct and extensive way to know the representation of well known peoples, however, for common people, there is poor knowledge for them to be recognized. In recent years, information extraction （IE） technologies have been used to automatically generate biography for any people with online information. One of the key challenges is the entity linking （EL） which can link biography sentence to corresponding entities. Currently the used general EL systems usually generate errors originated from entity name variation and ambiguity. Compared with general text, biography sentences possess unique yet rarely studied relational knowledge （RK） and temporal knowledge （TK）, which could sufficiently distinguish entities. This article proposed a new statistical framework called the knowledge enhanced EL （KeEL） system for automated biography construction. It utilizes commonsense knowledge like PK and TK to enhance Entity Linking. The performance of KeEL on Wikipedia data was evaluated. It is shown that, compared with state-of-the-art method, KeEL significantly improves the precision and recall of Entity Linking.展开更多
Knowledge bases(KBs)are often greatly incomplete,necessitating a demand for KB completion.Although XLORE is an English-Chinese bilingual knowledge graph,there are only 423,974 cross-lingual links between English insta...Knowledge bases(KBs)are often greatly incomplete,necessitating a demand for KB completion.Although XLORE is an English-Chinese bilingual knowledge graph,there are only 423,974 cross-lingual links between English instances and Chinese instances.We present XLORE2,an extension of the XLORE that is built automatically from Wikipedia,Baidu Baike and Hudong Baike.We add more facts by making cross-lingual knowledge linking,cross-lingual property matching and fine-grained type inference.We also design an entity linking system to demonstrate the effectiveness and broad coverage of XLORE2.展开更多
基金supported by the National Natural Science Foundation of China (No.82305376)2021 Special Research Project of TCM Science and Technology Development Plan of Jiangsu Province (ZT202120)+1 种基金Luo Linxiu Teacher Development Funding Project (LLX202308)National Key Research and Development Plan Intelligent Robot (2022YFB4703100).
文摘Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health conditions and it is commonly used alongside conventional medical treatments.With the development of artificial intelligence(AI)technology,new possibilities for improving the efficacy and precision of acupuncture have emerged.This study explored the combination of traditional acupuncture and AI technology from three perspectives:acupuncture diagnosis,prescription,and treatment evaluation.The study aimed to provide cutting-edge direction and theoretical assistance for the development of an acupuncture robot.
基金supported by the National Natural Science Foundation of China (61035004)
文摘Biography is a direct and extensive way to know the representation of well known peoples, however, for common people, there is poor knowledge for them to be recognized. In recent years, information extraction （IE） technologies have been used to automatically generate biography for any people with online information. One of the key challenges is the entity linking （EL） which can link biography sentence to corresponding entities. Currently the used general EL systems usually generate errors originated from entity name variation and ambiguity. Compared with general text, biography sentences possess unique yet rarely studied relational knowledge （RK） and temporal knowledge （TK）, which could sufficiently distinguish entities. This article proposed a new statistical framework called the knowledge enhanced EL （KeEL） system for automated biography construction. It utilizes commonsense knowledge like PK and TK to enhance Entity Linking. The performance of KeEL on Wikipedia data was evaluated. It is shown that, compared with state-of-the-art method, KeEL significantly improves the precision and recall of Entity Linking.
基金National Natural Science Foundation of China(NSFC)key project(No.61533018,No.U1736204 and No.61661146007)Ministry of Education and China Mobile Research Fund(No.20181770250)and THUNUS NExT Co-Lab.
文摘Knowledge bases(KBs)are often greatly incomplete,necessitating a demand for KB completion.Although XLORE is an English-Chinese bilingual knowledge graph,there are only 423,974 cross-lingual links between English instances and Chinese instances.We present XLORE2,an extension of the XLORE that is built automatically from Wikipedia,Baidu Baike and Hudong Baike.We add more facts by making cross-lingual knowledge linking,cross-lingual property matching and fine-grained type inference.We also design an entity linking system to demonstrate the effectiveness and broad coverage of XLORE2.
