Extractive Text Summarization with Supportive Images

Extractive Text Summarization with Supportive Images

The goal of this research is to investigate effects of images in text summarization. Most of the news contain images in the body part, however text summarization only studies text part of the document. It is shown that image captions and titles of texts can improve ROUGE score on text summarization task. However, images might not have captions or extracting captions from images can be challenging task for some datasets. 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 images 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: 

2017
  • Fall

Bize Ulaşın

Bilgisayar Mühendisliği Bölümü, Boğaziçi Üniversitesi,
34342 Bebek, İstanbul, Türkiye

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