Machine learning
Algorithms that learn patterns from data to power prediction or adaptation.
22 papers carry this theme
In these papers
- 01Advancements in Context Recognition for Edge Devices and Smart Eyewear: Sensors and ApplicationsFrancesca Palermo, Luca Casciano · 2025On-device context recognition for edge devices and eyewear.
- 02It ’ s just distributed computing: Rethinking AI governanceIndia (TRAI · 2025Frames 'AI' as varied ML applications on distributed computing.
- 03An empirical study of AI techniques in mobile applications ✩Haoye Tian b, Zhijie Wang c et al. · 2024Empirical study of AI/ML techniques in mobile apps.
- 04Article LIME-Mine: Explainable Machine Learning for User Behavior Analysis in IoT ApplicationsXiaobo Cai · 2024Extracts patterns from IoT user-activity traces.
- 05Identifying Hand-based Input Preference Based on Wearable EEGKaining Zhang∗ · 2024EEG-based method to evaluate hand-input preference.
- 06Machine Learning Algorithms for Improved Product Design User ExperienceXueli Wang, Bo Hu · 2024Combines PSO and ML for user-centric product design.
- 07Predictive Analytics for Website User BehaviorPawan Vankhede · 2024Random-forest predictive analytics for user behaviour.
- 08Clustering Methods for Adaptive e-Commerce User InterfacesAdam Wasilewski · 2023Clusters users (incl. AI methods) to drive adaptation.
- 09Tracing and Visualizing Human-ML/AI Collaborative Processes through Artifacts of Data WorkJen Rogers · 2023AutoML lowers barriers but still needs human intervention.
- 10A study of UX practitioners roles in designing real-world, enterprise ML systemsSabah Zdanowsk · 2022Studies real-world enterprise ML system design.
- 11Personalized User Interface Elements Recommendation SystemHao Liu, Xiangxian Li et al. · 2022Trains on user features and evaluations to recommend elements.
- 12Artificial intelligence in E‑Commerce: a bibliometric study and literature reviewBawack · 2021Synthesizes AI research in e-commerce.
- 13Computer Science ReviewMaaruf Ali, Peter S. Excell · 2021ML training and convergence underpin adaptive interfaces.
- 14Inertial Motion Tracking on Mobile and Wearable Devices: Recent Advancements and ChallengesZhipeng Song, Zhichao Cao et al. · 2021Learning-based inertial motion tracking on mobile/wearable IMUs.
- 15Personalization in Practice: Methods and ApplicationsDmitri Goldenberg · 2021Personalization as a key ML application across industries.
- 16An Effective Clustering‑Based Web Page Recommendation Framework for E‑Commerce WebsitesHarpreet Singh · 2020Clustering-based recommendation of web pages.
- 17Artificial intelligence in recommender systemsZhang · 2020Computational-intelligence and ML methods power the RS.
- 18Measuring and Improving User Experience Through Artificial Intelligence-Aided Design[Unknown · 2020AI-aided design (AIAD) for mobile-app UX.
- 19A survey of cyber‑physical system implementations of real‑time personalized interventionsRobert Steele · 2019Sensors plus ML enable real-time personalized health interventions.
- 20Investigating How Experienced UX Designers Effectively Work with Machine LearningQian Yang · 2018How experienced UX designers work with ML as a material.
- 21UX Design Innovation: Challenges for Working with Machine Learning as a Design MaterialGraham Dove, Kim Halskov · 2017Treats ML as a design material UX designers must work with.
- 22Machine Learning Techniques for Recommender Systems – A Comparative Case AnalysisBinu Thomas · 2011Surveys ML algorithms used to develop RSs.