HCI.TOPHCI, made easy

arrow_backBack to questions View categoryarrow_forward

Visualization, Analytics, and Data Understanding / Time Series Semantic Retrieval and Trend Analysis

VR users often cannot achieve immersive experiences due to cybersickness (e.g., eye strain, dizziness).

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

VR users often cannot achieve immersive experiences due to cybersickness (e.g., eye strain, dizziness).

UbiComp '24Early Prediction of Cybersickness in Virtual Reality Using a Large Language Model for Multimodal Time Series Data

Similar questions

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Welding engineers struggle to efficiently analyze multidimensional time series data, hindering quality monitoring.

IUI '25Cluster-Based Approach for Visual Anomaly Detection in Multivariate Welding Process Data Supported by User Guidance

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Decision-makers and the public struggle to identify misleading charts in time-series data.

CHI '25Visualization Guardrails: Designing Interventions Against Cherry-Picking in Interactive Data Explorers

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Non-technical experts struggle to participate in time-series model design, limiting practical application.

CHI '25Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Tasks

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Users struggle to precisely find needed trend features when analyzing time series data with tools.

IUI '24SlopeSeeker: A Search Tool for Exploring a Dataset of Quantifiable Trends

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Doctors and users struggle to understand the rationale behind time-series classification results.

UbiComp '24Time for an Explanation: A Mini-Review of Explainable Physio-Behavioural Time-Series Classification

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Wearable devices have insufficient accuracy and robustness for complex activity recognition.

UbiComp '24rTsfNet: A DNN Model with Multi-head 3D Rotation and Time Series Feature Extraction for IMU-based Human Activity Recognition

Related papers

Cluster-Based Approach for Visual Anomaly Detection in Multivariate Welding Process Data Supported by User Guidance

Josef Suschnigg, Belgin Mutlu, Matthias Burgholzer

Visualization Guardrails: Designing Interventions Against Cherry-Picking in Interactive Data Explorers

Maxim Lisnic, Zach Cutler, Marina Kogan

Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Tasks

Venkatesh Sivaraman, Anika Vaishampayan, Xiaotong Li

SlopeSeeker: A Search Tool for Exploring a Dataset of Quantifiable Trends

Alexander Bendeck, Dennis Bromley, Vidya Setlur

AutoTherm: A Dataset and Benchmark for Thermal Comfort Estimation Indoors and in Vehicles

Mark Colley, Sebastian Hartwig, Albin Zeqiri

iPose: Interactive Human Pose Reconstruction from Video

Jingyuan Liu, Li-Yi Wei, Ariel Shamir

Predicting the Noticeability of Dynamic Virtual Elements in Virtual Reality

Zhipeng Li, Yi Fei Cheng, Yukang Yan

Learning Custom Experience Ontologies via Embedding-based Feedback Loops

Ali Zaidi, Kelsey Turbeville, Kristijan Ivančić

Robust and Deployable Gesture Recognition for Smartwatches

Utkarsh Kunwar, Sheetal Borar, Moritz Berghofer

Detecting Input Recognition Errors and User Errors Using Gaze Dynamics in Virtual Reality

Naveen Sendhilnathan, Ting Zhang, Ben Lafreniere

Supporting Accessible Data Visualization Through Audio Data Narratives

Alexa F. Siu, Gene S-H Kim, Sile O'Modhrain

mTSeer: Interactive Visual Exploration of Models on Multivariate Time-series Forecast

Ke Xu, Jun Yuan, Yifang Wang