Text-Image-Video Summary Generation Using Joint Integer Linear Programming

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...

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Autores principales: Jangra, Anubhav, Jatowt, Adam, Hasanuzzaman, Mohammad, Saha, Sriparna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148046/
http://dx.doi.org/10.1007/978-3-030-45442-5_24
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author Jangra, Anubhav
Jatowt, Adam
Hasanuzzaman, Mohammad
Saha, Sriparna
author_facet Jangra, Anubhav
Jatowt, Adam
Hasanuzzaman, Mohammad
Saha, Sriparna
author_sort Jangra, Anubhav
collection PubMed
description 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.
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spelling pubmed-71480462020-04-13 Text-Image-Video Summary Generation Using Joint Integer Linear Programming Jangra, Anubhav Jatowt, Adam Hasanuzzaman, Mohammad Saha, Sriparna Advances in Information Retrieval Article 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. 2020-03-24 /pmc/articles/PMC7148046/ http://dx.doi.org/10.1007/978-3-030-45442-5_24 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Jangra, Anubhav
Jatowt, Adam
Hasanuzzaman, Mohammad
Saha, Sriparna
Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title_full Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title_fullStr Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title_full_unstemmed Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title_short Text-Image-Video Summary Generation Using Joint Integer Linear Programming
title_sort text-image-video summary generation using joint integer linear programming
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148046/
http://dx.doi.org/10.1007/978-3-030-45442-5_24
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AT jatowtadam textimagevideosummarygenerationusingjointintegerlinearprogramming
AT hasanuzzamanmohammad textimagevideosummarygenerationusingjointintegerlinearprogramming
AT sahasriparna textimagevideosummarygenerationusingjointintegerlinearprogramming

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