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Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey [article]

Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, Yaowei Wang, Yonghong Tian, Wen Gao
2024 arXiv   pre-print

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2023 pre-print
arXiv:2302.10035v1 fatcat:3eqblacftrgavcgtmq3m3nclly
In this work, we give a comprehensive survey of these models and hope this paper could provide new insights and helps fresh researchers to track the most cutting-edge works.  ...  Then, we introduce the task definition, key challenges, and advantages of multi-modal pre-training models (MM-PTMs), and discuss the MM-PTMs with a focus on data, objectives, network architectures, and  ...  arXiv NLP SC, 34 An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-Trained Language Models [45] 2021 arXiv NLP DC, 21 A multi-layer bidirectional transformer encoder for pre-trained  ... 
arXiv:2302.10035v3 fatcat:j2y4ti2f65aqbnap4ln436c7ci
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Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, Yaowei Wang, Yonghong Tian, Wen Gao. "Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey." arXiv (2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability [article]

Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
2023 arXiv   pre-print

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2022 pre-print
arXiv:2204.08570v1 fatcat:7c3pkxitrbhgxj6fytn6f3r644
In this paper, we give a comprehensive survey of GNNs in the computational aspects of privacy, robustness, fairness, and explainability.  ...  Due to their great ability in modeling graph-structured data, GNNs are vastly used in various applications, including high-stakes scenarios such as financial analysis, traffic predictions, and drug discovery  ...  For a comprehensive review of biases that occur in other phases such as training and evaluation of machine learning models on i.i.d data, please refer to the survey [152] .  ... 
arXiv:2204.08570v2 fatcat:sexh7tl3nfc6vl2porhfxcai54
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Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang. "A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability." arXiv (2023)

Spatio-Temporal Crime HotSpot Detection and Prediction: A Systematic Literature Review

Umair Muneer Butt, Sukumar Letchmunan, Fadratul Hafinaz Hassan, Mubashir Ali, Anees Baqir, Hafiz Husnain Raza Sherazi
2020 IEEE Access  

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The authors were unable to find a comprehensive study on crime hotspot detection and prediction while conducting this SLR.  ...  The primary objective of this study is to accumulate, summarize, and evaluate the state-ofthe-art for spatio-temporal crime hotspot detection and prediction techniques by conducting a systematic literature  ...  Besides, the majority of researchers survey data mining and machine learning techniques for crime detection and prediction [19] - [22] . Prerna et al.  ... 
doi:10.1109/access.2020.3022808 fatcat:szzqvkh64fdypotz6xwnrmujhm
DOAJ
Citation

Umair Muneer Butt, Sukumar Letchmunan, Fadratul Hafinaz Hassan, Mubashir Ali, Anees Baqir, Hafiz Husnain Raza Sherazi. "Spatio-Temporal Crime HotSpot Detection and Prediction: A Systematic Literature Review." IEEE Access (2020) 1-1

Predictive Policing and Crime Control in The United States of America and Europe: Trends in a Decade of Research and the Future of Predictive Policing

Ishmael Mugari, Emeka E. Obioha
2021 Social Sciences  

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This paper, which is based on a literature survey, examines predictive policing over the last decade (2010 to 2020).  ...  software, flawed data input, and the biased nature of some predictive software applications.  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/socsci10060234 fatcat:qwphkio6mjebnflbwclko2idne
DOAJ Szczepanski
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Ishmael Mugari, Emeka E. Obioha. "Predictive Policing and Crime Control in The United States of America and Europe: Trends in a Decade of Research and the Future of Predictive Policing." Social Sciences 10.6 (2021) 234

Location Prediction Models using Data Mining and Machine Learning

2020 International Journal of Engineering and Advanced Technology  

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A next location prediction model is a model that uses this data and can be designed as a combination of two or more models and techniques, but these have their own pros and cons.  ...  The paper is organized in a way so as to give readers insights and other noteworthy points and inferences from the papers surveyed.  ...  We have compiled a comprehensive analysis so that it is easy for the readers to interpret our survey.  ... 
doi:10.35940/ijeat.c6044.029320 fatcat:t6arkry335gftkj54dulsy5b54
Open Access
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"Location Prediction Models using Data Mining and Machine Learning." International Journal of Engineering and Advanced Technology 9.3 (2020) 3383-3390

Big Data and Predictive Reasonable Suspicion

Andrew Guthrie Ferguson
2014 Social Science Research Network  

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a past crime, and (3) situations involving officers predicting a future crime.  ...  Predictive Data Big data also promises another change in law enforcement techniques.  ... 
doi:10.2139/ssrn.2394683 fatcat:qkbfdteohjhltdv5zwuyznmryq
Citation

Andrew Guthrie Ferguson. "Big Data and Predictive Reasonable Suspicion." Social Science Research Network (2014)

Recent Advancements in Machine Learning For Cybercrime Prediction [article]

Lavanya Elluri, Varun Mandalapu, Piyush Vyas, Nirmalya Roy
2023 arXiv   pre-print

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2023 pre-print arXiv:2304.04819v1 fatcat:qjedgcoqknexzhx3u3rb4xor3a
Cybercrime is a growing threat to organizations and individuals worldwide, with criminals using sophisticated techniques to breach security systems and steal sensitive data.  ...  This paper aims to comprehensively survey the latest advancements in cybercrime prediction, highlighting the relevant research.  ...  (Mridha et al. (2021)) ANN and RF Accuracy -99% Utilizes Weka text mining tool to draw insights by classifying a given online scam dataset.  ... 
arXiv:2304.04819v2 fatcat:wbslxk4h4rgwtitkf6zhluxkvu
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Lavanya Elluri, Varun Mandalapu, Piyush Vyas, Nirmalya Roy. "Recent Advancements in Machine Learning For Cybercrime Prediction." arXiv (2023)

Predicting Social Unrest Events with Hidden Markov Models Using GDELT

Fengcai Qiao, Pei Li, Xin Zhang, Zhaoyun Ding, Jiajun Cheng, Hui Wang
2017 Discrete Dynamics in Nature and Society  

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In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability  ...  The framework utilizes the temporal burst patterns in GDELT event streams to uncover the underlying event development mechanics and formulates the social unrest event prediction as a sequence classification  ...  Acknowledgments This work is supported by the National Science Foundation of China (NSFC) under Grant nos. 71331008 and 61105124.  ... 
doi:10.1155/2017/8180272 fatcat:mm4clihn4bc3jmn2cvcqnxunby
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Fengcai Qiao, Pei Li, Xin Zhang, Zhaoyun Ding, Jiajun Cheng, Hui Wang. "Predicting Social Unrest Events with Hidden Markov Models Using GDELT." Discrete Dynamics in Nature and Society (2017) 1-13

A Systematic Review of Data Mining Studies in Parenting Research

Yanyan Liu, Jun Wei
2023 Journal of Educational Technology Development and Exchange  

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This study aims to provide a comprehensive review of the application of data mining methods in parenting research and to explore the insights offered by data mining algorithms in this domain.  ...  In this study, 31 academic parenting research studies, which utilized data mining techniques based on empirical data, are finally selected and thoroughly.  ...  The synthesis of data from multiple sources enhances the depth and scope of research, offering a more comprehensive comprehension and profound insights into the realm of parenting.  ... 
doi:10.18785/jetde.1602.08 fatcat:6mpc6qxdofgx5jl6lxoiqtihgy
Citation

Yanyan Liu, Jun Wei. "A Systematic Review of Data Mining Studies in Parenting Research." Journal of Educational Technology Development and Exchange 16.2 (2023) 126-144

Social prediction: a new research paradigm based on machine learning

Yunsong Chen, Xiaogang Wu, Anning Hu, Guangye He, Guodong Ju
2021 The Journal of Chinese Sociology  

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For many years, due to data and computing power constraints, quantitative research in social science has primarily focused on statistical tests to analyze correlations and causality, leaving predictions  ...  This shift will provide a rare opportunity for sociology in China to become the international frontier of computational social sciences and accelerate the construction of philosophy and social science  ...  Acknowledgements N/A. Authors' contribution Dr YC designed and instructed the study, Dr XW, Dr AH, Dr GH, Guodong Ju contributed in writing and revising.  ... 
doi:10.1186/s40711-021-00152-z fatcat:ooa4de6i5vhwtcwynqhq67qrru
DOAJ Szczepanski
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Yunsong Chen, Xiaogang Wu, Anning Hu, Guangye He, Guodong Ju. "Social prediction: a new research paradigm based on machine learning." The Journal of Chinese Sociology 8.1 (2021)

Introduction to Data Science and Machine Learning

P. Harika Reddy
2018 International Journal for Research in Applied Science and Engineering Technology  

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This paper gives a vast information about how actual data science has been evolving and how machine learning has been changing since ages .  ...  And the uses of data science and some brief information about how data science is so powerful and some use cases involving the implementation of data science in the real life.  ...  experimental it is empirical it is driven by testing out different algorithms into on real-world problems business problems and it is it starts from getting the data processing it making it ready for  ... 
doi:10.22214/ijraset.2018.6193 fatcat:x5e5bmn5ynfzbbzmbt6lzp5qqu
Open Access
Citation

P. Harika Reddy. "Introduction to Data Science and Machine Learning." International Journal for Research in Applied Science and Engineering Technology 6.6 (2018) 1322-1324

A Survey on Genomic Dataset for Predicting the DNA Abnormalities Using Ml

Siripuri Divya, Y. Bhavani, Thota Mahesh Kumar
2022 International Journal of Advanced Computer Science and Applications  

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Feature scaling machine learning techniques helps in predicting the sequence of genome for extrachromosomal amplification and predicting the tumor intensity in the human gene.  ...  Genomic data is used in bioinformatics for collecting, storing and processing the genomes of living things.  ...  Author had classified leukemia and paradigmatic using data mining techniques.  ... 
doi:10.14569/ijacsa.2022.0130537 fatcat:s57plpd23bbcdfnabnhbmjfs5i
Szczepanski
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Siripuri Divya, Y. Bhavani, Thota Mahesh Kumar. "A Survey on Genomic Dataset for Predicting the DNA Abnormalities Using Ml." International Journal of Advanced Computer Science and Applications 13.5 (2022)

Young male offenders in community-based rehabilitative programmes - self-reported history of antisocial behaviour predicts recidivism

Hanna Ginner Hau, AnnCharlotte Smedler
2011 International Journal of Social Welfare  

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SG 3 and 4 with the most extensive histories of antisocial behaviour were responsible for a significantly larger part of recidivism than expected.  ...  This was true for all crimes as well as crimes of violence specifically, confirming the subgroups identified based on the self-reports.  ...  The findings could be interpreted as a lack of insight into one's own difficulties in meeting social expectations.  ... 
doi:10.1111/j.1468-2397.2011.00792.x fatcat:bctdgs5eenbdlpfswg4luwclem
Citation

Hanna Ginner Hau, AnnCharlotte Smedler. "Young male offenders in community-based rehabilitative programmes - self-reported history of antisocial behaviour predicts recidivism." International Journal of Social Welfare 20.4 (2011) 413-420

Conformal predictions in multimedia pattern recognition

Vineeth N Balasubramanian
2011 ACM SIGMultimedia Records  

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and numerous opportunities for exposure and growth, and most importantly, for his never-failing support through every high and low of my PhD.  ...  and multimodal person recognition), and two regression-based applications (head pose estimation and saliency prediction in images).  ...  presented a comprehensive survey of techniques that are used to learn the distance metric matrix A in [3] , categorizing these techniques as shown in Figure 4 .1.  ... 
doi:10.1145/2069196.2069202 fatcat:pptvfth4bffxtllc3m665qodze
Citation

Vineeth N Balasubramanian. "Conformal predictions in multimedia pattern recognition." ACM SIGMultimedia Records 3.1 (2011) 23

From Recognition to Prediction: Analysis of Human Action and Trajectory Prediction in Video [article]

Junwei Liang
2021 arXiv   pre-print

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2020 pre-print
arXiv:2011.10670v1 fatcat:4syzjqn7ovabvnks6rdienna2y
2021 pre-print
arXiv:2011.10670v2 fatcat:wymnqpvmuva3rjj6hqwumxr5qq
This design hinders prediction performance in video data from diverse domains and unseen scenarios.  ...  However, human trajectory prediction still remains a challenging task, as scene semantics and human intent are difficult to model.  ...  Note that our techniques focus on predicting a few seconds into the future, and should not be useful for nonroutine activities.  ... 
arXiv:2011.10670v3 fatcat:mlom5zqk6jdvjndcsfwimpj7xu
Open Access Multiple Versions
Citation

Junwei Liang. "From Recognition to Prediction: Analysis of Human Action and Trajectory Prediction in Video." arXiv (2021)

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