# Online Behavioral Analysis with Application to Emotion State Identification

arXiv: https://arxiv.org/abs/2103.00356 · HTML: https://mlsanity.com/paper/2103.00356/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 23 references that are in the map.
- First posted on arXiv 27 Feb 2021.

## Built on by (most cited first, 1 of 1)

- [A Complete Discriminative Tensor Representation Learning for Two-Dimensional Correlation Analysis](https://mlsanity.com/paper/2103.00367/) (2021)

## Abstract (arXiv)

In this paper, we propose a novel discriminative model for online behavioral analysis with application to emotion state identification. The proposed model is able to extract more discriminative characteristics from behavioral data effectively and find the direction of optimal projection efficiently to satisfy requirements of online data analysis, leading to better utilization of the behavioral information to produce more accurate recognition results.