Extractive Text Summarization with Image Captions

Extractive Text Summarization with Image Captions

The goal of this research is to investigate effects of image captions in text summarization. Most of the news contain additional information such as images, image captions and titles in the body part, however text summarization only studies text of the document. It is shown that image captions and titles of texts can improve ROUGE score on text summarization task. However, I showed that image captions increase quality of the summarization in unsupervised models, too. Recent papers about text summarization study multi-document text summarization. Yet it looks harder task than single document summarization, more materials in multiple documents help to find salient information. I believe that image captions contain important aspects of news to understand them and find their summarizations.

Project Poster: 

Project Members: 

Abdullatif Köksal

Project Advisor: 

Arzucan Özgür

Project Status: 

Project Year: 

2018
  • Spring

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