Automatically generating a summary for asynchronous data can help users to keep up with the rapid growth of multi-modal information on the Internet. However, the current multi-modal systems usually generate summaries composed of text and images. In this paper, we propose a novel research problem of text-image-video summary generation (TIVS). We first develop a multi-modal dataset containing text documents, images and videos. We then propose a novel joint integer linear programming multi-modal summarization (JILP-MMS) framework. We report the performance of our model on the developed dataset.
CITATION STYLE
Jangra, A., Jatowt, A., Hasanuzzaman, M., & Saha, S. (2020). Text-image-video summary generation using joint integer linear programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12036 LNCS, pp. 190–198). Springer. https://doi.org/10.1007/978-3-030-45442-5_24
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