In this paper we hypothesize and empirically demonstrate that in order to increase tag prediction accuracy, the granularity of each user model has to be adapted ...

In this paper we hypothesize and empirically demonstrate that in order to increase tag prediction accuracy, the granularity of each user model has to be adapted ...

This paper hypothesize and empirically demonstrate that in order to increase tag prediction accuracy, the granularity of each user model has to be adapted ...

A Study on the Granularity of User Modeling for Tag Prediction. Frías-Martinez E., Cebrián M., Jaimes A. Expand. Publication type: Proceedings Article.

Feb 21, 2024 · Efforts were directed towards enhancing the understandability and interpretability of ML models, enabling users to gain a clearer understanding ...

model user knowledge and to use for prediction of student responses. Our results show that the finer the granularity of the skill model, the better we can.

In this paper we hypothesize and empirically demonstrate that in order to increase tag prediction accuracy, the granularity of each user model has to be adapted ...

Oct 21, 2024 · Multi-granularity modeling, which are central to overcoming these limitations by integrating diverse tasks, scenarios, modalities, and behaviors in the ...

We introduce Tracking at Any Granularity (TAG): a new task, model, and dataset for tracking arbitrary targets in videos. We seek a tracking method that ...

The paper has three main contributions: 1) We propose a method to discover the concept level of tags automatically. 2) We apply the method to a real-world tag ...