Zobrazeno 1 - 10
of 6 534 129
pro vyhledávání: '"Session A"'
Autor:
Russell Siler Jones
Spirituality is an important part of many clients'lives. It can be a resource for stabilization, healing, and growth. It can also be the cause of struggle and even harm. More and more therapists—those who consider themselves spiritual and those who
Autor:
Bauer, Josef1 (AUTHOR) josef.b.bauer@gmail.com, Jannach, Dietmar1 (AUTHOR)
Publikováno v:
User Modeling & User-Adapted Interaction. Jul2024, Vol. 34 Issue 3, p691-728. 38p.
Autor:
Li, Zihao1 (AUTHOR) zihao.li@student.uts.edu.au, Yang, Chao2 (AUTHOR) chao.yang@ouc.edu.cn, Chen, Yakun1 (AUTHOR) yakun.chen@student.uts.edu.au, Wang, Xianzhi1 (AUTHOR) xianzhi.wang@uts.edu.au, Chen, Hongxu1 (AUTHOR) hongxu.chen@uts.edu.au, Xu, Guandong3 (AUTHOR) guandong.xu@uts.edu.au, Yao, Lina4 (AUTHOR) lina.yao@unsw.edu.au, Sheng, Michael5 (AUTHOR) michael.sheng@mq.edu.au
Publikováno v:
ACM Computing Surveys. Feb2025, Vol. 57 Issue 2, p1-37. 37p.
Autor:
Liu, Xiangyu1 liuxiangyu@usst.edu.cn, Dai, Chenyun2 chenyundai@sjtu.edu.cn, Liu, Jionghui3 jhliu22@m.fudan.edu.cn, Yuan, Yangyang4 jhliu22@m.fudan.edu.cn
Publikováno v:
Bioengineering (Basel). Aug2024, Vol. 11 Issue 8, p811. 11p.
Autor:
Spomer, Alyssa M.1 (AUTHOR) AlyssaMSpomer@gillettechildrens.com, Conner, Benjamin C.2 (AUTHOR), Schwartz, Michael H.3,4 (AUTHOR), Lerner, Zachary F.5 (AUTHOR), Steele, Katherine M.1 (AUTHOR)
Publikováno v:
PLoS ONE. 11/18/2024, Vol. 19 Issue 11, p1-19. 19p.
Recent advancements in session-based recommendation models using deep learning techniques have demonstrated significant performance improvements. While they can enhance model sophistication and improve the relevance of recommendations, they also make
Externí odkaz:
http://arxiv.org/abs/2411.09152
Multiparty session types provide a type discipline for ensuring communication safety, deadlock-freedom and liveness for multiple concurrently running participants. The original formulation of MPST takes the top-down approach, where a global type spec
Externí odkaz:
http://arxiv.org/abs/2411.07452
Session-based recommendation (SR) models aim to recommend top-K items to a user, based on the user's behaviour during the current session. Several SR models are proposed in the literature, however,concerns have been raised about their susceptibility
Externí odkaz:
http://arxiv.org/abs/2410.21892
Session-based recommendation is the task of predicting the next item a user will interact with, often without access to historical user data. In this work, we introduce Sequential Masked Modeling, a novel approach for encoder-only transformer archite
Externí odkaz:
http://arxiv.org/abs/2410.11150
Session-based Recommendation (SBR), seeking to predict a user's next action based on an anonymous session, has drawn increasing attention for its practicability. Most SBR models only rely on the contextual transitions within a short session to learn
Externí odkaz:
http://arxiv.org/abs/2410.10296