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User-curated image collections: Modeling and recommendation

Yuncheng Li, Tao Mei, Yang Cong, Jiebo Luo
2015 2015 IEEE International Conference on Big Data (Big Data)  
., image collection modeling and similarity measurement.  ...  In this paper, we aim to design a novel recommendation system that can provide users with image collections relevant to individual personal preferences and interests.  ...  . 1) Main Database: Bing click-through logs contain a list of user queries and the clicked images.  ... 
doi:10.1109/bigdata.2015.7363803 dblp:conf/bigdataconf/LiMCL15 fatcat:ebw6hirf6jbz7iqdrzp5dhzysy

Modelling and Analysing Behaviours and Emotions via Complex User Interactions [article]

Mohamed Mostafa
2019 arXiv   pre-print
We contextualise this research project with a wider review and critical analysis of the current psycholinguistics, artificial intelligence and human-computer interaction literature, which reveals a gap  ...  from text posted by users.  ...  Key Elements of the Model According to the output of the statistical analysis presented in Table 6 .31 (linear regression) and The dataset used to build this model is based upon a number of users (N=391  ... 
arXiv:1902.07683v1 fatcat:xeqntpaysve7pd77oxu3lu3vta

Mediation of user models for enhanced personalization in recommender systems

Shlomo Berkovsky, Tsvi Kuflik, Francesco Ricci
2007 User modeling and user-adapted interaction  
Provision of personalized recommendations to users requires accurate modeling of their interests and needs.  ...  It provides a generic user modeling data representation model, demonstrates its compatibility with existing recommendation techniques, and discusses the general steps of the mediation.  ...  of the Istituto Trentino di Cultura-the Center for Scientific and Technological Research (ITCirst) in Trento, Italy.  ... 
doi:10.1007/s11257-007-9042-9 fatcat:d3lr5r3rafgrno5qnp6rtjqpt4

User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems [article]

Yang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng, Helen Meng
2022 arXiv   pre-print
In this paper, we propose a novel framework, namely USDA, to incorporate the sequential dynamics of dialogue acts for predicting user satisfaction, by jointly learning User Satisfaction Estimation and  ...  Finally, USDA leverages the sequential transitions of both content and act features in the dialogue to predict the user satisfaction.  ...  ACKNOWLEDGMENTS This research/paper was supported by the Center for Perceptual and Interactive Intelligence (CPII) Ltd under the Innovation and Technology Commission's InnoHK scheme.  ... 
arXiv:2202.02912v1 fatcat:a7i2amxrjfh4rezbhinpjwd47y

Neuroscientific User Models: The Source of Uncertain User Feedback and Potentials for Improving Recommendation and Personalisation [article]

Kevin Jasberg, Sergej Sizov
2018 arXiv   pre-print
The interplay of cognition model and decoder functions lead to different model-based properties of decision-making.  ...  Whenever research on this topic is done, there is a very strong system-centric view in which user variation is something undesirable and should be modelled with the eye to eliminate.  ...  Acknowledgements Computational support and infrastructure was provided by the Centre for Information and Media Technology (ZIM) at the University of Duesseldorf (Germany).  ... 
arXiv:1804.10861v1 fatcat:b2p7zpnjnjfhvaci5h32lwif2q

Visualization and User-Modeling for Browsing Personal Photo Libraries

Baback Moghaddam, Qi Tian, Neal Lesh, Chia Shen, Thomas S. Huang
2004 International Journal of Computer Vision  
An efficient computational technique for subspace weighting and re-estimation leads to a simple user-modeling framework whereby the system can learn to display query results based on layout examples (or  ...  Monte Carlo simulations with machine-generated layouts as well as pilot user studies have demonstrated the ability of this framework to model or "mimic" users, by automatically generating layouts according  ...  This work was supported in part by Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA and National Science Foundation Grants CDA 96-24396 and EIA 99-75019. Notes 1.  ... 
doi:10.1023/b:visi.0000004834.62090.74 fatcat:fkwdrhpzfvf7bdm5wqyxx3gx44

User Interaction Models for Disambiguation in Programming by Example

Mikaël Mayer, Gustavo Soares, Maxim Grechkin, Vu Le, Mark Marron, Oleksandr Polozov, Rishabh Singh, Benjamin Zorn, Sumit Gulwani
2015 Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology - UIST '15  
Moreover, both models are perceived as useful, and the proactive active-learning based model has a slightly higher preference regarding the users' confidence in the result.  ...  The other model uses active learning to ask directed example-based questions to the user on the test input data over which the user intends to run the synthesized program.  ...  Mikael, Gustavo, Vu, and Alex were each supported by a oneyear position at MSR, and Maxim was supported by a sixmonth position at MSR.  ... 
doi:10.1145/2807442.2807459 dblp:conf/uist/MayerSGLMPSZG15 fatcat:uq62mdnznbcrld6dsuv5kh2azm

Singing Vocal Enhancement For Cochlear Implant Users Based On Deep Learning Models

Tom Gajecki
2018 Zenodo  
and subjectively through two different perceptual experiments involving normal hearing (NH) subjects and CI recipients.  ...  This work proposes deep convolutional auto-encoders (DCAEs), a deep recurrent neural network (DRNN), a multilayer perceptron (MLP) and non-negative matrix factorization (NMF) to be evaluated objectively  ...  MUSHRA For this test, a robust statistical analysis was adopted to minimize the potential effects of outliers and non-normality.  ... 
doi:10.5281/zenodo.1303049 fatcat:tzpqzurebfcobk2xkpyuo557nm

Context pre-modeling: an empirical analysis for classification based user-centric context-aware predictive modeling

Iqbal H. Sarker, Hamed Alqahtani, Fawaz Alsolami, Asif Irshad Khan, Yoosef B. Abushark, Mohammad Khubeb Siddiqui
2020 Journal of Big Data  
Based on the context pre-modeling tasks and classification methods, we experimentally analyze user-centric smartphone usage behavioral activities utilizing their contextual datasets.  ...  This paper mainly explores the role of major context pre-modeling tasks, such as context vectorization by defining a good numerical measure through transformation and normalization, context generation  ...  of applications and relevant contextual data in different dimensions.  ... 
doi:10.1186/s40537-020-00328-3 fatcat:lz4lkkhai5g2hlnhb5nc74y6pq

Personalized robot-assisted dressing using user modeling in latent spaces

Fan Zhang, Antoine Cully, Yiannis Demiris
2017 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
and the robot caused by user movements; 2) the online update of the dressing trajectory based on the user movement limitations modeled with the Gaussian Process Latent Variable Model in a latent space  ...  However, the user movements during the dressing process are rarely taken into account, which often leads to the failures of the planned trajectory and may put the user at risk.  ...  ., Principal Component Analysis [20] ) often fail to accurately model human movements.  ... 
doi:10.1109/iros.2017.8206206 dblp:conf/iros/ZhangCD17 fatcat:2dicokpnivg7lisphwgrgepqve

Towards Effective Research-Paper Recommender Systems and User Modeling based on Mind Maps [article]

Joeran Beel
2017 arXiv   pre-print
While user-modeling and recommender systems successfully utilize items like emails, news, and movies, they widely neglect mind-maps as a source for user modeling.  ...  The recommender system builds user models based on the mind maps, and recommends research papers based on the user models.  ...  110 This chapter has been published as: Beel, Joeran, Bela Gipp, Ammar Shaker, and Nick Friedrich.  ... 
arXiv:1703.09109v1 fatcat:egcsnop34jbi7p2urz34pxr3vi

MyGraine: Predicting Migraines Through Various Machine Learning Models Utilizing User-Inputted Data

Rebecca S. Zhu, Rucha Dave
2020 International Journal of High School Research  
Through this project, multiple types of machine learning models were trained to predict the occurrence of migraines in individuals.  ...  Finally, a user-friendly website was developed. This website took in biometrics and user-inputted data to display the probability of getting a migraine, using the logistic regression model.  ...  Cynthia Pitkin from Nashua High School South and Professor Marek Petrik from the University of New Hampshire for their valuable feedback and help.  ... 
doi:10.36838/v2i4.13 fatcat:dgvu2rnk7fbxrdqoxlumuonrhi

System Level User Behavior Biometrics using Fisher Features and Gaussian Mixture Models

Yingbo Song, Malek Ben Salem, Shlomo Hershkop, Salvatore J. Stolfo
2013 2013 IEEE Security and Privacy Workshops  
We propose a machine learning-based method for biometric identification of user behavior, for the purpose of masquerade and insider threat detection.  ...  We show that this system achieves promising results for user behavior modeling and identification, and surpasses previous works in this area. IEEE Security and Privacy Workshops  ...  In this case, an additional subspace projection step using Principle Component Analysis is typically used, before Fishers criterion is applied.  ... 
doi:10.1109/spw.2013.33 dblp:conf/sp/SongSHS13 fatcat:37igfgv7yjdcncwvkcu5h4k32y

User-Aware Image Tag Refinement via Ternary Semantic Analysis

Jitao Sang, Changsheng Xu, Jing Liu
2012 IEEE transactions on multimedia  
To tackle the problem of tag refinement, we propose a method of Ranking based Multi-correlation Tensor Factorization (RMTF), to jointly model the ternary relations among user, image, and tag, and further  ...  We also show attractive performances on two potential applications as the by-products of the ternary relation analysis.  ...  TABLE I STATISTICS I OF NUS-WIDE-USER15 TABLE III FIVE III NEAREST TAGS IN THE LEARNED TAG SUBSPACE FOR EACH OF THE FOUR SELECTED TAGS TABLE IV FIVE IV NEAREST IMAGES IN THE LEARNED IMAGE SUBSPACE  ... 
doi:10.1109/tmm.2012.2188782 fatcat:lbllgvb4fncnzk7zuwsmwkozwi

Unsupervised Learning For Effective User Engagement on Social Media [article]

Thai Pham, Camelia Simoiu
2016 arXiv   pre-print
We compare Principal Component Analysis (PCA) and sparse Autoencoder to a baseline method where the data are only centered and scaled, on each of two models: Linear Regression and Regression Tree.  ...  In this paper, we investigate the effectiveness of unsupervised feature learning techniques in predicting user engagement on social media.  ...  We then fit the training and test data through these weights and biases to obtain the processed data for subsequent analysis.  ... 
arXiv:1611.03894v1 fatcat:72anuth6xfhmldphm4jez6scgm
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