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Subject

A Survey of the State-of-the-art Aspect Summarization Methods
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측면 요약 기술의 최신 연구 동향

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Type
Proceeding
Author
Dahoon Gu (군산대학교) Byung-Won On (군산대학교) Hyunjun Jung (군산대학교) Dongwon Jeong (군산대학교)
Journal
Korean Institute of Information Technology Proceedings of KIIT Conference The Proceedings of the 2022 KIIT Summer Conference
Published
2022.6
Pages
251 - 254 (4page)

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A Survey of the State-of-the-art Aspect Summarization Methods
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With the development of the Internet, big data is being generated in various forms in various fields. One type of big data is text data, which is unstructured data, and automatic text summarization methods have been actively studied as one of main applications. Existing automatic text summarization techniques are categorized to extractive summarization and abstractive summarization. However, if one only want to know specific information within a document, existing summarization methods are not suitable because those are working based on the generic comprehensive concepts. As one of the solutions, recently, an aspect summarization method has been propsed for the first time, based on the existing automatic text summarization. With the advent of various social network services (SNS) and communities, aspect summarization are becoming increasingly important because a vast amount of review data for a specific product is collected from SNS and various communities. Therefore, in this paper, we first describe the details of the major aspect summarization methods, and then compare them to the existing summarization ones.

Contents

요약
Abstract
Ⅰ. 서론
Ⅱ. 기존의 자동 텍스트 요약 기술과 비교한 측면 요약 기술
Ⅲ. 결론
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