Multi-Modal Summary Generation using Multi-Objective Optimization
May 19, 2020 Β· Declared Dead Β· π Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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Authors
Anubhav Jangra, Sriparna Saha, Adam Jatowt, Mohammad Hasanuzzaman
arXiv ID
2005.09252
Category
cs.IR: Information Retrieval
Citations
14
Venue
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Last Checked
3 months ago
Abstract
Significant development of communication technology over the past few years has motivated research in multi-modal summarization techniques. A majority of the previous works on multi-modal summarization focus on text and images. In this paper, we propose a novel extractive multi-objective optimization based model to produce a multi-modal summary containing text, images, and videos. Important objectives such as intra-modality salience, cross-modal redundancy and cross-modal similarity are optimized simultaneously in a multi-objective optimization framework to produce effective multi-modal output. The proposed model has been evaluated separately for different modalities, and has been found to perform better than state-of-the-art approaches.
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