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

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

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

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

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

lightbulbPractical problemTime Series Semantic Retrieval and Trend Analysis

Doctors struggle to accurately understand patient emotions in complex emotional scenarios.

UbiComp '24pSCOUTER: Time-Series Emotion Classification Using Contactless Measured Multimodal Biosignals in Medical Diagnosis

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

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Learning Custom Experience Ontologies via Embedding-based Feedback Loops

Ali Zaidi, Kelsey Turbeville, Kristijan Ivančić

Robust and Deployable Gesture Recognition for Smartwatches

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

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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