Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Guo Yikai"'
Publikováno v:
Redai dili, Vol 44, Iss 8, Pp 1435-1448 (2024)
The widespread adoption of information and communication technologies has reshaped the spatial dynamics of the catering industry, rendering the coopetition relations between take-out and traditional restaurants in spatial distribution increasingly in
Externí odkaz:
https://doaj.org/article/8ef379b722e848b39fc32e3b1372ab37
Autor:
Li, Guozheng, Wang, Peng, Ke, Wenjun, Guo, Yikai, Ji, Ke, Shang, Ziyu, Liu, Jiajun, Xu, Zijie
Relation extraction (RE) aims to identify relations between entities mentioned in texts. Although large language models (LLMs) have demonstrated impressive in-context learning (ICL) abilities in various tasks, they still suffer from poor performances
Externí odkaz:
http://arxiv.org/abs/2404.17809
Relation extraction (RE) is an important task that aims to identify the relationships between entities in texts. While large language models (LLMs) have revealed remarkable in-context learning (ICL) capability for general zero and few-shot learning,
Externí odkaz:
http://arxiv.org/abs/2404.17807
Dialogue relation extraction (DRE) aims to extract relations between two arguments within a dialogue, which is more challenging than standard RE due to the higher person pronoun frequency and lower information density in dialogues. However, existing
Externí odkaz:
http://arxiv.org/abs/2404.17802
Autor:
Luo, Haoran, E, Haihong, Tang, Zichen, Peng, Shiyao, Guo, Yikai, Zhang, Wentai, Ma, Chenghao, Dong, Guanting, Song, Meina, Lin, Wei, Zhu, Yifan, Tuan, Luu Anh
Publikováno v:
ACL 2024
Knowledge Base Question Answering (KBQA) aims to answer natural language questions over large-scale knowledge bases (KBs), which can be summarized into two crucial steps: knowledge retrieval and semantic parsing. However, three core challenges remain
Externí odkaz:
http://arxiv.org/abs/2310.08975
Autor:
Luo, Haoran, E, Haihong, Yang, Yuhao, Yao, Tianyu, Guo, Yikai, Tang, Zichen, Zhang, Wentai, Wan, Kaiyang, Peng, Shiyao, Song, Meina, Lin, Wei, Zhu, Yifan, Tuan, Luu Anh
Publikováno v:
NeurIPS 2024
Beyond traditional binary relational facts, n-ary relational knowledge graphs (NKGs) are comprised of n-ary relational facts containing more than two entities, which are closer to real-world facts with broader applications. However, the construction
Externí odkaz:
http://arxiv.org/abs/2310.05185
Autor:
Luo, Haoran, E, Haihong, Yang, Yuhao, Guo, Yikai, Sun, Mingzhi, Yao, Tianyu, Tang, Zichen, Wan, Kaiyang, Song, Meina, Lin, Wei
Publikováno v:
ACL 2023
Link Prediction on Hyper-relational Knowledge Graphs (HKG) is a worthwhile endeavor. HKG consists of hyper-relational facts (H-Facts), composed of a main triple and several auxiliary attribute-value qualifiers, which can effectively represent factual
Externí odkaz:
http://arxiv.org/abs/2305.06588
Autor:
Luo, Haoran, E, Haihong, Yang, Yuhao, Zhou, Gengxian, Guo, Yikai, Yao, Tianyu, Tang, Zichen, Lin, Xueyuan, Wan, Kaiyang
Publikováno v:
AAAI 2023
Complex query answering (CQA) is an essential task for multi-hop and logical reasoning on knowledge graphs (KGs). Currently, most approaches are limited to queries among binary relational facts and pay less attention to n-ary facts (n>=2) containing
Externí odkaz:
http://arxiv.org/abs/2211.13469
Autor:
Tian, Xuemeng, Guo, Yikai, Ge, Bin, Yuan, Xiaoguang, Zhang, Hang, Yang, Yuting, Ke, Wenjun, Li, Guozheng
Publikováno v:
In Knowledge-Based Systems 3 December 2024 305
Publikováno v:
In Knowledge-Based Systems 11 January 2024 283