• Title, Summary, Keyword: 의견마이닝

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Analysis of limitations using only adjectives sentiment word dictionary (형용사만을 사용한 의견어 사전의 한계점 분석)

  • Yu, WonHui;Ji, Hye-Seong;Yang, Yeong-Uk;Lim, HeuiSeok
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.373-375
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    • 2011
  • 최근 많은 연구가 되고 있는 오피니언 마이닝은 의견어 사전의 구축이 가장 기본적으로 선행되어야 하는 연구이다. 오피니언 마이닝의 의견어 사전 구축 연구는 영어를 중심으로 많은 연구가 진행 되었다. 하지만 형용사 위주의 의견어 사전 구축으로 많은 부분의 문제들이 해결되는 영어에 비해서 한국어는 여러 가지 품사와 문장구조를 고려하여 의견어 사전을 구축해야한다. 이것을 실험으로 밝히기 위하여 형용사로만 구성되어진 의견어 사전을 구축하고 영화평에 적용하여 분석해 봄으로써 형용사로만 구성되어진 의견어 사전의 한계점을 확인한다. 실험은 세종계획 말뭉치에서 나타나는 형용사로 구성된 의견어 사전을 구축하고 네이버 랩에서 제공하는 영화평을 형용사로 구성된 의견어 사전으로 의견 분석하여 시행하였다. 분석 결과 재현율 약 50%, 정확률 약 60%정도의 성능을 보였다.

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Friend Recommendation System Using Opinion Mining (오피니언 마이닝을 이용한 친구 추천 시스템)

  • Hwang, Su-Jin;Yoon, Jae-Yeol;Kim, Iee-Joon;Kim, Ung-Mo
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.1188-1190
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    • 2011
  • 오피니언 마이닝은 웹에 있는 문서를 분석하여 작성자의 의견을 요약된 형태로 보여주는 기술이다. 오피니언 마이닝을 이용해 문서 작성자의 주관적 의견을 알 수 있고 이를 통해 작성자의 성향이나 관심사와 같은 정보를 얻을 수 있다. 많은 네티즌들은 소셜 네트워크 서비스를 통해 자신의 의견이 담긴 글을 타인과 공유 하며 네트워크상의 인맥을 넓혀 나간다. 오피니언 마이닝을 통해 개인이 작성한 글들을 분석하여 관심사를 파악하고 비슷한 관심사를 가진 친구를 추천하는 친구 추천 시스템을 제안한다.

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Expansion of Opinion Mining based on Entity Association Network Model (개체연관망 모델에 의한 오피니언마이닝의 확장)

  • Kim, Keun-Hyung
    • The KIPS Transactions:PartD
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    • v.18D no.4
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    • pp.237-244
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    • 2011
  • Opinion Mining summarizes with classifying sensitive opinions of customers in huge online customer reviews for the attributes of products or services by positive and negative opinions. Because the customers represent their interests through subjective opinions as well as objective facts, the existing opinion mining techniques, which can analyze just the sensitive opinions, need to be expanded.. In this paper, We propose the novel entity association network model which expands the existing opinion mining techniques. The entity association model can not only represent positive and negative degree of the sensitive opinions, but also can represent the degree of the associations and relative importances between entities. We designed and implemented the customer reviews analysis system based on the entity association network model. We recognized that the system can represent more abundant information than the existing opinion mining techniques.

A Sentiment Classification Method Using Context Information in Product Review Summarization (상품 리뷰 요약에서의 문맥 정보를 이용한 의견 분류 방법)

  • Yang, Jung-Yeon;Myung, Jae-Seok;Lee, Sang-Goo
    • Journal of KIISE:Databases
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    • v.36 no.4
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    • pp.254-262
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    • 2009
  • As the trend of e-business activities develop, customers come into contact with products through on-line shopping sites and lots of customers refer product reviews before the purchasing on-line. However, as the volume of product reviews grow, it takes a great deal of time and effort for customers to read and evaluate voluminous product reviews. Lately, attention is being paid to Opinion Mining(OM) as one of the effective solutions to this problem. In this paper, we propose an efficient method for opinion sentiment classification of product reviews using product specific context information of words occurred in the reviews. We define the context information of words and propose the application of context for sentiment classification and we show the performance of our method through the experiments. Additionally, in case of word corpus construction, we propose the method to construct word corpus automatically using the review texts and review scores in order to prevent traditional manual process. In consequence, we can easily get exact sentiment polarities of opinion words in product reviews.

A Study on Extracting Ideas from Documents and Webpages in the Field of Idea Mining (아이디어 마이닝 분야에서 문헌과 웹페이지의 아이디어 발췌에 대한 연구)

  • Lee, Tae-Young
    • Journal of the Korean Society for information Management
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    • v.29 no.1
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    • pp.25-43
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    • 2012
  • The ideas and quasi-ideas useful for human's creation were drawn out from documents and webpages with extraction methods used in idea mining, opinion mining, and topic signal mining. The extraction methods comprised (1) decisive cue phrases, (2) cue figures and sounds, (3) contextual signals, and (4) discourse segmentations, They tested on the idea samples, such as thoughts, plans, opinions, writings, figures, sounds, and formulas. Methods (1), (3), and (4) received largely positive evaluation, judging the efficiency of 4 methods by F measure, a mixture of recall and precision ratio. In particular, decisive cue phrase method was effective to search idea and contextual signal method was effective to detect quasi-idea.

Study on the social issue sentiment classification using text mining (텍스트마이닝을 이용한 사회 이슈 찬반 분류에 관한 연구)

  • Kang, Sun-A;Kim, Yoo Sin;Choi, Sang Hyun
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.5
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    • pp.1167-1173
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    • 2015
  • The development of information and communication technology like SNS, blogs, and bulletin boards, was provided a variety of places where you can express your thoughts and comments and allowing Big Data to grow, many people reveal the opinion of the social issues in SNS such as Twitter. In this study, we would like to pre-built sentimental dictionary about social issues and conduct a sentimental analysis with structured dictionary, to gather opinions on social issues that are created on twitter. The data that I used is "bikini", "nakkomsu" including tweet. As the result of analysis, precision is 61% and F1- score is 74%. This study expect to suggest the standard of dictionary construction allowing you to classify positive/negative opinion on specific social issues.

A Study on Web Mining System for Real-Time Monitoring of Opinion Information Based on Web 2.0 (의견정보 모니터링을 위한 웹 마이닝 시스템에 관한 연구)

  • Joo, Hae-Jong;Hong, Bong-Hwa;Jeong, Bok-Cheol
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.1
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    • pp.149-157
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    • 2010
  • As the use of the Internet has recently increased, the demand for opinion information posted on the Internet has grown. However, such resources only exist on the website. People who want to search for information on the Internet find it inconvenient to visit each website. This paper focuses on the opinion information extraction and analysis system through Web mining that is based on statistics collected from Web contents. That is, users' opinion information which is scattered across several websites can be automatically analyzed and extracted. The system provides the opinion information search service that enables users to search for real-time positive and negative opinions and check their statistics. Also, users can do real-time search and monitoring about other opinion information by putting keywords in the system. Proposed technologies proved to have outstanding capabilities in comparison to existing ones through tests. The capabilities to extract positive and negative opinion information were assessed. Specifically, test movie review sentence testing data was tested and its results were analyzed.

Spam Filtering using Opinion Mining (오피니언 마이닝을 이용한 스팸 필터링)

  • Oh, Jin-Soo;Ryu, Joon-Suk;Kim, Ung-Mo
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.745-746
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    • 2009
  • 오늘날 사람들의 의견을 제시하는 공간은 폐쇄적인 인쇄물이나 수동적인 답변 수준을 벗어나 무한의 공간을 가지는 웹에서 이루어지고 있다. 불특정 다수를 대상으로 하며 정형화된 틀을 없는, 더욱 유용한 의견을 많이 얻을 수 있는 특징을 가졌기 때문에, 이를 위해 오피니언 마이닝에 대한 연구가 활발히 진행되고 있다. 기본적으로 오피니언 마이닝은 해당 분야에 대한 정확한 정보를 찾는 것을 목적으로 하지만, 그러한 정보를 제외한 나머지 부분에 대해서도 충분히 유용하게 사용할 수 있다. 본 논문에서는 그 나머지 부분을 이용하여 무분별하게 등록되고 있는 스팸성 댓글을 효과적으로 필터링 할 수 있는 방법을 제안한다.

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Usage of Leader Weights for Opinion mining (리더 가중치를 활용한 오피니언 마이닝)

  • Cho, Kyung Soo;Ryu, Joon-suk;Kim, Young Hee;Kim, Ung-mo
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.848-851
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    • 2010
  • 인터넷 사용의 증가와 함께 최근 많은 양의 정보가 인터넷에 쏟아지고 있다. 이들 정보는 다른 사람의 생각을 알고 싶어하는 정보 수집 연구자들에게는 매우 유용한 정보이다. 현재 존재하는 오피니언 마이닝 기법은 매우 다양하다. 그러나 이러한 기법들은 모든 의견들을 동일한 영향력을 지닌 것으로 취급한다. 하지만 현실에서는 모든 의견이 동일한 영향력을 가지고 있지는 않다. 이런 문제점 해결을 위해서 우리는 새로운 오피니언 마이닝 기법을 제안한다.

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Web Contents Mining System for Real-Time Monitoring of Opinion Information based on Web 2.0 (웹2.0에서 의견정보의 실시간 모니터링을 위한 웹 콘텐츠 마이닝 시스템)

  • Kim, Young-Choon;Joo, Hae-Jong;Choi, Hae-Gill;Cho, Moon-Taek;Kim, Young-Baek;Rhee, Sang-Yong
    • Journal of Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.68-79
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    • 2011
  • This paper focuses on the opinion information extraction and analysis system through Web mining that is based on statistics collected from Web contents. That is, users' opinion information which is scattered across several websites can be automatically analyzed and extracted. The system provides the opinion information search service that enables users to search for real-time positive and negative opinions and check their statistics. Also, users can do real-time search and monitoring about other opinion information by putting keywords in the system. Proposing technique proved that the actual performance is excellent by comparison experiment with other techniques. Performance evaluation of function extracting positive/negative opinion information, the performance evaluation applying dynamic window technique and tokenizer technique for multilingual information retrieval, and the performance evaluation of technique extracting exact multilingual phonetic translation are carried out. The experiment with typical movie review sentence and Wikipedia experiment data as object as that applying example is carried out and the result is analyzed.