# A Survey of Data Representation for Multi-Modality Event Detection and Evolution
## 7 Datasets and Evaluation  
### Datasets  
Most of the existing works used self-collected datasets and these datasets are not public. So, it is hard to compare their performance. However, there are also some public datasets were used to evaluate multi-modality event detection. So, we only give the comparison between some specific works on several public datasets in this section. 1. Social Event Detection (SED) dataset. The SED datasets are provided by the MediaEval challenge. The goal of this task is to discover social events of interest from the mass of user-generated Flickr multi-modality content and the metadata surrounding it. It released four subsets in 2011-2014: SED2011 [113], SED2012 [114], SED2013 [115], SED2014 [116]. Different years released different challenges. The statistic information of the datasets is shown in Table 5. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Models** & **Modality Data Type** & **Characteristic** \\ \hline
[107] & News video, web news articles and news blogs & Topic evolution based on various online platforms and based on the interest of users. \\ \hline
[108] & Web video, news article & Topic evolution with various media information, and enables the visualization and exploration of different information. \\ \hline
[109] & Web video & A concise structure that shows the evolution of events associated with the representative text keywords and visual shots. \\ \hline
[110] & Images, text & Text and image are combined to analysis and deliver the storyline and structural information to provide topic evolution sketch. \\ \hline
[111] & Web news, newspaper, TV program, Weibo & Events in a very long time period are detected and traced, and a multimedia-based visualization is provided. \\ \hline
[112] & Web news with image & Storyline extraction and reconstruction, a unified algorithm is designed to extract all effective storylines. \\ \hline
[99] & Web news, image & An incremental learning strategy is adopting informative textual and visual topics of social events over time to help understand events and their evolutionary trends. \\ \hline
[106] & News Text, image & Tracking topics detected in certain continuous time periods. Link all detected topics in different time periods to form topic trajectories over time. \\ \hline
[113] & Web news, images & Nonparametric online multimodal tracking module that allows the tracked model to evolve backwards to undo undesirable model updates, which helps alleviate the model drift problem of social event tracking. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of the multi-modality event evolution models. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Data** & **Time** & **Introduction** \\ \hline SED2011 & 2011 & \begin{tabular}{c} Contains 73,645 images of five cities: Amsterdam, Barcelona, London, Paris and Rome. \\ \end{tabular} \\ \hline SED2012 & 2012 & \begin{tabular}{c} Contains 167,332 images of five cities: Barcelona, Madrid, \\ Cologne, Hamburg and Hannover \\ \end{tabular} \\ \hline SED2013 & 2013 & \
\begin{tabular}{c} Contains 427,370 images and 1327 videos with XML \\ timestamps, geographic information, tags, titles, \\ descriptions, etc. \\ \end{tabular} \\ \hline SED2014 & 2014 &
\begin{tabular}{c} SED 2014 released two datasets. One dataset contains \\ 362,578 images and the other dataset contains 110,541 \\ images. The metadata of the two datasets are available. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Datasets of SED 2011–2014 for event detection. 2. Multi-modality Social Event Dataset. This dataset is a multi-modality social event dataset (short for MMSE) downloaded from Flickr and has different versions. The datasets are composed of image and text data.