Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Jia, Pengyue"'
Autor:
Liu, Ziwei, Liu, Qidong, Wang, Yejing, Wang, Wanyu, Jia, Pengyue, Wang, Maolin, Liu, Zitao, Chang, Yi, Zhao, Xiangyu
In various domains, Sequential Recommender Systems (SRS) have become essential due to their superior capability to discern intricate user preferences. Typically, SRS utilize transformer-based architectures to forecast the subsequent item within a seq
Externí odkaz:
http://arxiv.org/abs/2408.11451
Autor:
Jia, Pengyue, Liu, Yiding, Li, Xiaopeng, Wang, Yuhao, Du, Yantong, Han, Xiao, Wei, Xuetao, Wang, Shuaiqiang, Yin, Dawei, Zhao, Xiangyu
Worldwide geolocalization aims to locate the precise location at the coordinate level of photos taken anywhere on the Earth. It is very challenging due to 1) the difficulty of capturing subtle location-aware visual semantics, and 2) the heterogeneous
Externí odkaz:
http://arxiv.org/abs/2405.14702
Autor:
Jia, Pengyue, Wang, Yejing, Du, Zhaocheng, Zhao, Xiangyu, Wang, Yichao, Chen, Bo, Wang, Wanyu, Guo, Huifeng, Tang, Ruiming
Deep Recommender Systems (DRS) are increasingly dependent on a large number of feature fields for more precise recommendations. Effective feature selection methods are consequently becoming critical for further enhancing the accuracy and optimizing s
Externí odkaz:
http://arxiv.org/abs/2403.12660
Search engines are crucial as they provide an efficient and easy way to access vast amounts of information on the internet for diverse information needs. User queries, even with a specific need, can differ significantly. Prior research has explored t
Externí odkaz:
http://arxiv.org/abs/2312.15450
Autor:
Jia, Pengyue, Liu, Yiding, Zhao, Xiangyu, Li, Xiaopeng, Hao, Changying, Wang, Shuaiqiang, Yin, Dawei
Query expansion, pivotal in search engines, enhances the representation of user information needs with additional terms. While existing methods expand queries using retrieved or generated contextual documents, each approach has notable limitations. R
Externí odkaz:
http://arxiv.org/abs/2310.19056
Predicting the number of infections in the anti-epidemic process is extremely beneficial to the government in developing anti-epidemic strategies, especially in fine-grained geographic units. Previous works focus on low spatial resolution prediction,
Externí odkaz:
http://arxiv.org/abs/2202.06257
Publikováno v:
Cybernetics & Systems; 2024, Vol. 55 Issue 1, p184-202, 19p
