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Emotion Analysis for Personality Inference from EEG Signals

Guozhen Zhao, Yan Ge, Biying Shen, Xingjie Wei, Hao Wang
2018 IEEE Transactions on Affective Computing  
) but also the discriminative power of the classification accuracies between five personality traits in each category of emotion.  ...  Features extracted from EEG signals and subjective ratings enter the SVM classifier as inputs to predict five dimensions of personality traits.  ...  digital footprint on social network (e.g., Facebook Likes).  ... 
doi:10.1109/taffc.2017.2786207 fatcat:4kaud5ou3rhmhkftycfwibjzgq

Predicting demographics, moral foundations, and human values from digital behaviours

Kyriaki Kalimeri, Mariano G. Beiró, Matteo Delfino, Robert Raleigh, Ciro Cattuto
2019 Computers in Human Behavior  
Along with the demographic data, we collected self-reported assessments on validated psychometric questionnaires for moral traits and basic human values and combined this information with passively collected  ...  for the moral traits and human values.  ...  The need for understanding human factors via digital data sparkled an ever-growing interest in automatic recognition of personality traits due to its association with important life aspects, including  ... 
doi:10.1016/j.chb.2018.11.024 fatcat:ljlsx4ksy5g3xgmhmi4qiewmpe

Metafeatures-based Rule-Extraction for Classifiers on Behavioral and Textual Data [article]

Yanou Ramon, David Martens, Theodoros Evgeniou, Stiene Praet
2021 arXiv   pre-print
To address this problem, we develop and test a rule-extraction methodology based on higher-level, less-sparse metafeatures.  ...  Machine learning models on behavioral and textual data can result in highly accurate prediction models, but are often very difficult to interpret.  ...  We want to predict health or personality traits [42] of users based on the Facebook pages they have "liked".  ... 
arXiv:2003.04792v3 fatcat:7iqpuqgokfet7kkkkdwcooih3u

Machine learning for the educational sciences

Sven Hilbert, Stefan Coors, Elisabeth Kraus, Bernd Bischl, Alfred Lindl, Mario Frei, Johannes Wild, Stefan Krauss, David Goretzko, Clemens Stachl
2021 Review of Education  
Youyou et al. (2015) , for example, showed that ML algorithms can use digital footprints in social media data to predict self-reported personality more accurately compared to predictions based on peer-ratings  ...  The analysis of digital footprints or smartphone usage have been extensively shown to be related to latent psychological constructs, such as the Big Five personality traits (see Harari et al., 2019; Stachl  ... 
doi:10.1002/rev3.3310 fatcat:uh6uszc7ingyrcoks3luzlfnne

Learning User Attributes via Mobile Social Multimedia Analytics

Liqiang Nie, Luming Zhang, Meng Wang, Richang Hong, Aleksandr Farseev, Tat-Seng Chua
2017 ACM Transactions on Intelligent Systems and Technology  
Learning user attributes from mobile social media is a fundamental basis for many applications, such as personalized and targeting services.  ...  Extensive evaluations on a real-world dataset thoroughly demonstrated the effectiveness of our proposed model.  ...  via an adjacency matrix.  ... 
doi:10.1145/2963105 fatcat:gqtvbai7zvc5tbscz53jwtejcu

Educational data mining: A survey and a data mining-based analysis of recent works

Alejandro Peña-Ayala
2014 Expert systems with applications  
on descriptive and predictive models were identified.  ...  A profile of the EDM works was organized as a raw data base, which was transformed into an ad-hoc data base suitable to be mined.  ...  In addition, Kabakchieva, Stefanova, and Kisimov (2011) seek patterns to predict student performance at the university based on their personal and pre-university traits; Wang and Heffernan (2011)  ... 
doi:10.1016/j.eswa.2013.08.042 fatcat:4ce647o5j5gwnm46gmilw3chg4

MOESM1 of The RiBaTox web tool: selecting methods to assess and manage the diverse problem of chemical pollution in surface waters

Kees Kramer, Frank Sleeuwaert, Guy Engelen, Christin MĂźller, Werner Brack, Leo Posthuma
2019 Figshare  
The sensitivity (correct predictions for binders) was found to be greater than 90% and specificity (correct predictions for non-binders) 80% for predictions in the model domain.  ...  Within SOLUTIONS project, both receptor mediated model predictions have been used by partners involved in Chemical Analytical tools.  ...  These four lines of evidence (LOE) are integrated in a systematic and transparent WOE approach, based on a decision matrix.  ... 
doi:10.6084/m9.figshare.9923471 fatcat:4qjsdqautbhhbd7jxzh7osx3hi

A survey on computer aided diagnosis for ocular diseases

Zhuo Zhang, Ruchir Srivastava, Huiying Liu, Xiangyu Chen, Lixin Duan, Damon Wing Kee Wong, Chee Keong Kwoh, Tien Yin Wong, Jiang Liu
2014 BMC Medical Informatics and Decision Making  
It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients.  ...  Section "Result: predicting ocular diseases based on genetic information" concerns studies relating genomic informatics to disease prediction.  ...  Each of these heterogeneous data sources (image features, personal profile data, SNP data) is likely to contain a different perspective on the disease risk of an individual, based on the pathological,  ... 
doi:10.1186/1472-6947-14-80 pmid:25175552 pmcid:PMC4163681 fatcat:4lvv4oils5euhitmqeigcmhf74

Occlusion Detection and Index-based Ear Recognition

Madeena Sultana, Padma Polash Paul, Marina Gavrilova
2015 Journal of WSCG  
, and A is the sparse blur matrix.  ...  The main principles of CS MRI are that the images to be reconstructed can be sparsely represented; measurement matrix is irrelevant to sparse transform Permission to make digital or hard copies of all  ...  Conference and SME Workshop on HDR imaging, Oporto Portugal, April 2013.  ... 
dblp:journals/jwscg/SultanaPG15 fatcat:uisp4vxs2vecrpjyy6cugbd2oa

Graph Neural Networks in IoT: A Survey [article]

Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Sikun Guo, Lihua Cai, Robert Gutierrez, Bradford Campbell, Laura E. Barnes, Mehdi Boukhechba
2022 arXiv   pre-print
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily lives: healthcare, home, transportation, manufacturing, supply chain, and so on.  ...  [318] proposed a semi-supervised spatial-temporal learning framework that incorporates environmental contextual factors and sparse real-time parking data into environmental factors and sparse real-time  ...  Kampman et al. used a trimodal architecture to blend video clips, audio, and text data to predict Big Five Personality Trait scores [116] .  ... 
arXiv:2203.15935v2 fatcat:jkqg5ukg5fezbewu5mr5hqsp4e

Environment-Specific vs. General Knowledge and Their Role in Pro-environmental Behavior

Sonja Maria Geiger, Mattis Geiger, Oliver Wilhelm
2019 Frontiers in Psychology  
In a multivariate study (n = 214), latent data modeling was employed to explore the internal factor structure of environmental knowledge, its relationship with general knowledge and explanatory power on  ...  We tested competing factor models and uncovered a general factor of environmental knowledge. The main novel finding of the study concerns its relationship with general knowledge.  ...  Patterns of mean-level change in personality traits across the life course: a meta-analysis of longitudinal studies. Psychol.  ... 
doi:10.3389/fpsyg.2019.00718 pmid:31001174 pmcid:PMC6454026 fatcat:dn3hqezm3bdk3cx72vphwrc2v4

Green Learning: Introduction, Examples and Outlook [article]

C.-C. Jay Kuo, Azad M. Madni
2022 arXiv   pre-print
However, the high carbon footprint yielded by larger and larger DL networks becomes a concern for sustainability.  ...  They include subspace approximation, unsupervised and supervised representation learning, supervised discriminant feature selection, and feature space partitioning.  ...  Then, one can compute the percentage of correct predictions. The higher the prediction accuracy, the higher the discriminant power.  ... 
arXiv:2210.00965v1 fatcat:k4ql32st5fcd5iapipqpqo6zfa

Assessment of Individual Differences in Online Social Networks Using Machine Learning

Arman Idani, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository, John Rust, Pushmeet Kohli
Prior research shows that psychological traits such as personality can be predicted using these digital footprints, although current state-of-the-art accuracy is below psychometric standards of reliability  ...  In the learning stage, instead of linear regression models, I use an ensemble of decision trees which are able to distinguish scenarios where the same observations on digital data can mean different things  ...  The types of behaviour common on a social network determines which personality traits or which facets of each trait are more predictable using digital footprints stored on the social network.  ... 
doi:10.17863/cam.16924 fatcat:6wjir7wf4neybb5yjjubkswlyq

Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow

Dominik Buschmann, Anna Haberberger, Benedikt Kirchner, Melanie Spornraft, Irmgard Riedmaier, Gustav Schelling, Michael W. Pfaffl
2016 Nucleic Acids Research  
Hypotheses based on flawed experimental conditions can be inconsistent and even misleading.  ...  This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions.  ...  This high variation in human populations as such is based on various factors.  ... 
doi:10.1093/nar/gkw545 pmid:27317696 pmcid:PMC5291277 fatcat:4fixci2cbbfyjc4bj6tq72eqdq

BIOSIG 2020 - Komplettband

2020 Biometrics and Electronic Signatures  
We further study the effect of masked face probes on the behaviour of three top-performing face recognition systems, two academic solutions and one commercial off-the-shelf (COTS) system.  ...  The effect of wearing a mask on face recognition in a collaborative environment is currently sensitive yet understudied issue.  ...  Arun Ross for his contributions and valuable comments on the early draft of this paper. We also would like to thank Dr. Gerald Early and Dr.  ... 
dblp:conf/biosig/X20 fatcat:hkqvegujqbatdlopbzclkxdive
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