Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Wancheng Ni"'
Publikováno v:
IEEE Access, Vol 7, Pp 146282-146300 (2019)
Chinese question entity discovery and linking (QEDL) may encounter short texts and small-scale annotated datasets, which may invalidate certain machine learning algorithms. In this paper, we propose a progressive joint framework for Chinese QEDL, whi
Externí odkaz:
https://doaj.org/article/a5698ce6e00f4c78a28457735fcb6302
Autor:
Ziwei Jin, Jiaxing Shang, Wancheng Ni, Liang Zhao, Dajiang Liu, Baohua Qiang, Wu Xie, Geyong Min
Publikováno v:
Information Sciences. 604:170-196
Publikováno v:
2022 IEEE Conference on Games (CoG).
Publikováno v:
2022 7th International Conference on Computer and Communication Systems (ICCCS).
Publikováno v:
SCIENTIA SINICA Informationis. 50:540-550
At the frontier of artificial intelligence research, human-computer gaming (HCG) technology has become a research hotspot. It provides an effective experimental environment and approach to exploring the intrinsic growth mechanism and verifying key te
Publikováno v:
Knowledge-Based Systems. 254:109659
Publikováno v:
ICCCS
Opponent modeling is a significant method in imperfect information games. And intention recognition is regarded as the important but difficult in opponent modeling. This paper focuses on the task of tactical intention recognition in computational war
Publikováno v:
IEEE Access, Vol 7, Pp 146282-146300 (2019)
Chinese question entity discovery and linking (QEDL) may encounter short texts and small-scale annotated datasets, which may invalidate certain machine learning algorithms. In this paper, we propose a progressive joint framework for Chinese QEDL, whi
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 48:177-194
Recommender systems are widely used for suggesting books, education materials, and products to users by exploring their behaviors. In reality, users’ preferences often change over time, leading to studies on time-dependent recommender systems. Howe
Publikováno v:
CoNLL
Text classification plays a crucial role for understanding natural language in a wide range of applications. Most existing approaches mainly focus on long text classification (e.g., blogs, documents, paragraphs). However, they cannot easily be applie