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72 24-四月-2024 22:50 3 KB 程龚 前一版本
71 26-三月-2024 10:14 3 KB 程龚 前一版本 | 最新版本
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Gong Cheng
Gong Cheng

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Gong Cheng is a professor at the Department of Computer Science and Technology, Nanjing University. His research interests include __big data search__, __knowledge graph__, and __neuro-symbolic reasoning__ with applications to knowledge computing platforms, data search engines, question answering systems, etc. His research has been published at conferences and in journals including WWW and TKDE, and has received or been nominated for seven best paper awards. He served as PC co-chairs of ISWC 2024 and CCKS 2023.
Gong Cheng is a professor at the Department of Computer Science and Technology, Nanjing University. His research interests include __big data search__, __knowledge graph__, and __neuro-symbolic reasoning__ with applications to data search engines, knowledge computing platforms, question answering systems, etc. His research has been published at conferences and in journals including WWW and TKDE, and has received or been nominated for seven best paper awards from ISWC, ESWC, and COLING. He served as PC co-chairs of ISWC 2024 and CCKS 2023.
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* __data search engines__: more effective data search engines, featuring data fusion, retrieval, ranking, summarization, recommendation, etc.; [[ [ISWC 2023|https://doi.org/10.1007/978-3-031-47240-4_2] | [TKDE 2023|https://doi.org/10.1109/TKDE.2021.3095309] | [SIGIR 2022|https://doi.org/10.1145/3477495.3531729] ]
* __knowledge graph search__: search algorithms for large knowledge graphs, e.g., efficient approximation algorithms for Steiner Tree problems; [[ [WWW 2023|https://doi.org/10.1145/3543507.3583257] | [WWW 2021|https://doi.org/10.1145/3442381.3449900] | [WWW 2020|https://doi.org/10.1145/3366423.3380110] ]
* __complex question answering__: neuro-symbolic methods for question answering with applications to complex tasks such as problem solving. [[ [AAAI 2023|https://doi.org/10.1609/aaai.v37i11.26543] | [ACL 2022|https://doi.org/10.18653/v1/2022.acl-long.494] | [AAAI 2021|https://doi.org/10.1609/aaai.v35i15.17570]]
* __data search engines__: more effective data search engines, featuring data fusion, retrieval, ranking, summarization, recommendation, etc.; [[ SIGIR 2024 | SIGIR 2024 | [ISWC 2023|https://doi.org/10.1007/978-3-031-47240-4_2] | [TKDE 2023|https://doi.org/10.1109/TKDE.2021.3095309] ]
* __knowledge graph search__: search algorithms for large knowledge graphs, e.g., efficient approximation algorithms for Steiner Tree problems; [[ WWW2024 | [WWW 2023|https://doi.org/10.1145/3543507.3583257] | [WWW 2021|https://doi.org/10.1145/3442381.3449900] | [WWW 2020|https://doi.org/10.1145/3366423.3380110] ]
* __large language model and reasoning__: fusion of neural large language models with symbolic reasoning over knowledge bases for solving complex problems. [[ [AAAI 2023|https://doi.org/10.1609/aaai.v37i11.26543] | [ACL 2022|https://doi.org/10.18653/v1/2022.acl-long.494] | [AAAI 2021|https://doi.org/10.1609/aaai.v35i15.17570]]
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*ISWC 2022-2023
*ISWC 2022-2024
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*ADMA 2023
*IEEE BigData 2024
*ADMA 2023-2024
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