TY - GEN
T1 - Efforts towards Combining Graphics, Uncertainty, and Semantics: A Survey
AU - Gao, Yuan
AU - Rafi, Muhammad
PY - 2020/3/23
Y1 - 2020/3/23
N2 - Modeling the real world is a basic but vital task in computer science. Graphics, uncertainty, and semantics are three key aspects of understanding structure and "why" when handling complex relationships with imperfect or unknown information. The combination of the three aspects can provide a systematic and effective method for modeling the real world. This paper presents a survey of the efforts towards combining these aspects. One branch of the efforts is to combine graphics and uncertainty as probabilistic graphical models (PGMs), and then associate PGMs with semantics. The other branch is to combine graphics and semantics as graph-based knowledge representations, and then add the probability to handle uncertainty. We introduce the models and methods involved in these efforts and discuss the expressiveness, pros and cons of them. Finally, we suggest future work in this domain.
AB - Modeling the real world is a basic but vital task in computer science. Graphics, uncertainty, and semantics are three key aspects of understanding structure and "why" when handling complex relationships with imperfect or unknown information. The combination of the three aspects can provide a systematic and effective method for modeling the real world. This paper presents a survey of the efforts towards combining these aspects. One branch of the efforts is to combine graphics and uncertainty as probabilistic graphical models (PGMs), and then associate PGMs with semantics. The other branch is to combine graphics and semantics as graph-based knowledge representations, and then add the probability to handle uncertainty. We introduce the models and methods involved in these efforts and discuss the expressiveness, pros and cons of them. Finally, we suggest future work in this domain.
KW - Graph-based knowledge representation
KW - Markov logic network
KW - Probabilistic graphical model
KW - Probabilistic soft logic
KW - Semantic link network
KW - Semantic network
UR - https://ieeexplore.ieee.org/document/9044080/
UR - http://www.scopus.com/inward/record.url?scp=85083242798&partnerID=8YFLogxK
U2 - 10.1109/SKG49510.2019.00022
DO - 10.1109/SKG49510.2019.00022
M3 - Conference publication
SN - 978-1-7281-5824-2
T3 - Proceedings - 15th International Conference on Semantics, Knowledge and Grids: On Big Data, AI and Future Interconnection Environment, SKG 2019
SP - 81
EP - 88
BT - Proceedings - 15th International Conference on Semantics, Knowledge and Grids
A2 - Zhuge, Hai
A2 - Sun, Xiaoping
PB - IEEE
T2 - 2019 15th International Conference on Semantics, Knowledge and Grids (SKG)
Y2 - 17 September 2019 through 18 September 2019
ER -