To achieve this goal, we propose a novel multi-modal supervised latent dirichlet allocation (mm-SLDA) for social event classification. Our proposed mm-SLDA has ...

The aim of this paper is to automati- cally identify the interesting events from massive social me- dia data, which are useful to browse, search and monitor.

(1) It can effectively exploit the multi-modality and the supervised information of social events jointly. (2) It is suitable to large-scale data analysis by ...

The aim of this paper is to automatically identify the interesting events from massive social media data, which are useful to browse, search and monitor ...

We propose a novel multi-modal supervised latent dirichlet allocation (mm-SLDA) topic model for social event classification, which can effectively exploit the.

To achieve this goal, we propose a novel multi-modal supervised latent dirichlet allocation (mm-SLDA) for social event classification. Our proposed mm-SLDA has ...

To deal with these issues, we propose a novel boosted multi-modal supervised Latent Dirichlet Allocation. (BMM-SLDA) for social event classification. Our BMM- ...

To achieve this goal, we propose a novel multi-modal supervised latent dirichlet allocation (mm-SLDA) for social event classification. Our proposed mm-SLDA has ...

The proposed multi-modal supervised Latent Dirichlet Allocation topic model for social event classification. For details, please refer to the corresponding text ...

The aim of this paper is to automatically identify the interesting events from massive social media data, which are useful to browse, search and monitor social ...