A Cross-Domain Perspective to Clustering with Uncertainty

被引:0
|
作者
Pileggi, Salvatore F. [1 ]
机构
[1] Univ Technol Sydney, Fac Engn & IT, Sch Comp Sci, Ultimo, Australia
来源
关键词
Clustering; Uncertainty Modelling; Uncertainty Management; Unsupervised Learning; Data Analysis; Data Mining; EFFICIENT; ALGORITHMS; FRAMEWORK; IMPACT;
D O I
10.1007/978-3-031-63783-4_22
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Clustering in presence of uncertainty may be considered, at the same time, to be a pressing need and a challenge to effectively address many real-world problems. This concise literature review aims to identify and discuss the associated body of knowledge according to a cross-domain perspective. A semi-systematic methodology has allowed the selection of 68 papers, with a priority on the most recent contributions. The analysis has re-marked the relevance of the topic and has made explicit a trend to domain-specific solutions over generic-purpose approaches. On one side, this trend enables a more specific set of solutions within specific communities; on the other side, the resulting distributed approach is not always well-integrated in the mainstream and may generate a further fragmentation of the body of knowledge, mostly because of some lack of abstraction in the definition of specific problems. While these gaps are largely understandable within the research community, a lack of implementations to provide ready-to-use resources is overall critical, looking at a more and more computational and data intensive world.
引用
收藏
页码:295 / 308
页数:14
相关论文
共 50 条
  • [1] Cross-Genre and Cross-Domain Detection of Semantic Uncertainty
    Szarvas, Gyoergy
    Vincze, Veronika
    Farkas, Richard
    Mora, Gyoergy
    Gurevych, Iryna
    [J]. COMPUTATIONAL LINGUISTICS, 2012, 38 (02) : 335 - 367
  • [2] Cross-Domain Contrastive Learning for Time Series Clustering
    Peng, Furong
    Luo, Jiachen
    Lu, Xuan
    Wang, Sheng
    Li, Feijiang
    [J]. THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 8, 2024, : 8921 - 8929
  • [3] Semantic clustering-based cross-domain recommendation
    Kumar, Anil
    Kumar, Nitesh
    Hussain, Muzammil
    Chaudhury, Santanu
    Agarwal, Sumeet
    [J]. 2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM), 2014, : 137 - 141
  • [4] A Compact Representation for Cross-Domain Short Text Clustering
    Nunez-Reyes, Alba
    Villatoro-Tello, Esau
    Ramirez-de-la-Rosa, Gabriela
    Sanchez-Sanchez, Christian
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE, MICAI 2016, PT I, 2017, 10061 : 16 - 26
  • [5] ADDRESSING UNCERTAINTY AND CONFLICTS IN CROSS-DOMAIN DATA PROVENANCE
    Moitra, Abha
    Barnett, Bruce
    Crapo, Andrew
    Dill, Stephen J.
    [J]. MILITARY COMMUNICATIONS CONFERENCE, 2010 (MILCOM 2010), 2010, : 912 - 917
  • [6] Modeling Domains as Distributions with Uncertainty for Cross-Domain Recommendation
    Zhu, Xianghui
    Jin, Mengqun
    Zhang, Hengyu
    Meng, Chang
    Zhang, Daoxin
    Li, Xiu
    [J]. PROCEEDINGS OF THE 47TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2024, 2024, : 2517 - 2521
  • [7] Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation
    Li, Jichang
    Li, Guanbin
    Shi, Yemin
    Yu, Yizhou
    [J]. 2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021, 2021, : 2505 - 2514
  • [8] CONTRAST UNCERTAINTY DOMAIN ALIGNMENT FOR CROSS-DOMAIN PANCREATIC IMAGE SEGMENTATION
    Fan, Ligang
    Bian, Yun
    Zhu, Weifang
    Shi, Fei
    Chen, Xinjian
    Shao, Chengwei
    Xiang, Dehui
    [J]. 2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI, 2023,
  • [9] Learning Cross-domain Information Transfer for Location Recognition and Clustering
    Gopalan, Raghuraman
    [J]. 2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2013, : 731 - 738
  • [10] Cross-Domain Clustering Performed by Transfer of Knowledge across Domains
    Samanta, Suranjana
    Selvan, A. Tirumarai
    Das, Sukhendu
    [J]. 2013 FOURTH NATIONAL CONFERENCE ON COMPUTER VISION, PATTERN RECOGNITION, IMAGE PROCESSING AND GRAPHICS (NCVPRIPG), 2013,