Zobrazeno 1 - 10
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pro vyhledávání: '"Chatti A"'
Publikováno v:
Contabilitate şi Informatică de Gestiune, Vol 23, Iss 3, Pp 530-550 (2024)
Research Question: How has the diffusion of IPSAS in the African region been influenced by contextual factors, external pressures, and the current status of adoption and implementation across African countries? Motivation: Africa seems to be the reg
Externí odkaz:
https://doaj.org/article/5eac3c33dc454e90819c2c1ff3d1136b
Autor:
Guesmi, Mouadh, Chatti, Mohamed Amine, Joarder, Shoeb, Ain, Qurat Ul, Alatrash, Rawaa, Siepmann, Clara, Vahidi, Tannaz
Explainable recommender systems (RS) have traditionally followed a one-size-fits-all approach, delivering the same explanation level of detail to each user, without considering their individual needs and goals. Further, explanations in RS have so far
Externí odkaz:
http://arxiv.org/abs/2306.05809
Autor:
Guesmi, Mouadh, Chatti, Mohamed Amine, Joarder, Shoeb, Ain, Qurat Ul, Siepmann, Clara, Ghanbarzadeh, Hoda, Alatrash, Rawaa
Significant attention has been paid to enhancing recommender systems (RS) with explanation facilities to help users make informed decisions and increase trust in and satisfaction with the RS. Justification and transparency represent two crucial goals
Externí odkaz:
http://arxiv.org/abs/2305.17034
Autor:
Beeler, Chris, Subramanian, Sriram Ganapathi, Sprague, Kyle, Chatti, Nouha, Bellinger, Colin, Shahen, Mitchell, Paquin, Nicholas, Baula, Mark, Dawit, Amanuel, Yang, Zihan, Li, Xinkai, Crowley, Mark, Tamblyn, Isaac
This paper provides a simulated laboratory for making use of Reinforcement Learning (RL) for chemical discovery. Since RL is fairly data intensive, training agents `on-the-fly' by taking actions in the real world is infeasible and possibly dangerous.
Externí odkaz:
http://arxiv.org/abs/2305.14177
Providing system-generated explanations for recommendations represents an important step towards transparent and trustworthy recommender systems. Explainable recommender systems provide a human-understandable rationale for their outputs. Over the las
Externí odkaz:
http://arxiv.org/abs/2305.11755
Autor:
Siepmann, Clara, Chatti, Mohamed Amine
Trust is long recognized to be an important factor in Recommender Systems (RS). However, there are different perspectives on trust and different ways to evaluate it. Moreover, a link between trust and transparency is often assumed but not always furt
Externí odkaz:
http://arxiv.org/abs/2304.08094
Research on Human-Centered Learning Analytics (HCLA) has provided demonstrations of a successful co-design process for LA tools with different stakeholders. However, there is a need for 'quick and dirty' methods to allow the low-cost design of LA ind
Externí odkaz:
http://arxiv.org/abs/2304.01711
Autor:
Chatti, Mohamed Amine, Guesmi, Mouadh, Vorgerd, Laura, Ngo, Thao, Joarder, Shoeb, Ain, Qurat Ul, Muslim, Arham
Despite the acknowledgment that the perception of explanations may vary considerably between end-users, explainable recommender systems (RS) have traditionally followed a one-size-fits-all model, whereby the same explanation level of detail is provid
Externí odkaz:
http://arxiv.org/abs/2304.00969
Open Learning Analytics (OLA) is an emerging research area that aims at improving learning efficiency and effectiveness in lifelong learning environments. OLA employs multiple methods to draw value from a wide range of educational data coming from va
Externí odkaz:
http://arxiv.org/abs/2303.12395
Human-Centered learning analytics (HCLA) is an approach that emphasizes the human factors in learning analytics and truly meets user needs. User involvement in all stages of the design, analysis, and evaluation of learning analytics is the key to inc
Externí odkaz:
http://arxiv.org/abs/2303.12392