• Title/Summary/Keyword: Web opinion information

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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 the 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.

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.

Empirical Sentiment Classification Using Psychological Emotions and Social Web Data (심리학적 감정과 소셜 웹 자료를 이용한 감성의 실증적 분류)

  • Chang, Moon-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.563-569
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    • 2012
  • The studies of opinion mining or sentiment analysis have been the focus with social web proliferation. Sentiment analysis requires sentiment resources to decide its polarity. In the existing sentiment analysis, they have been built resources designed with intensity of sentiment polarity and decided polarity of opinion using the ones. In this paper, I will present sentiment categories for not only polarity of opinion but also the basis of positive/negative opinion. I will define psychological emotions to primary sentiments for the reasonable classification. And I will extract the informations of sentiment from social web texts for the actual distribution of sentiments in social web. Re-classifying primary sentiments based on extracted sentiment information, I will organize sentiment categories for the social web. In this paper, I will present 23 categories of sentiment by using proposed method.

Causal model analysis between quantity and quality for deriving ranking model of Online reviews (온라인리뷰의 랭킹모델링을 위한 양과 질의 인과모형 분석)

  • Lee, Changyong;Kim, Keunhyung
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.1-16
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    • 2019
  • Purpose The purpose of this study is to analyze causal relationship between quantity and quality for deriving ranking model of Online reviews. Thus, we propose implications for deriving the ranking model for retrieving Online reviews more effectively. Design/methodology/approach We collected Online review from Tripadvisor web sites which might be a kind of world-famous tourism web sites. We transformed the natural text reviews to quantified data which consists of quantified positive opinions, quantified negative opinions, quantified modification opinions, reviews lengths and grade scores by using opinion mining technologies in R package. We executed corelation and regression analysis about the data. Findings According to the empirical analysis result, this study confirmed that the review length influenced positive opinion, negative opinion and modification opinion. We also confirmed that negative opinion and modification opinion influenced the grade score.

Web Contents Mining System for Opinion Information Searching Engine (의견정보 검색엔진을 위한 웹 콘텐츠 마이닝 시스템)

  • Joo, Hae-Jong;Park, Young-Bae;Choi, Hae-Gil
    • The Journal of Information Technology
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    • v.12 no.3
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    • pp.7-17
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    • 2009
  • This research is about the design of an opinion drawing and analysis system through statistical based Web Mining of web contents, where data of opinions are automatically drawn and analyzed concerning web documents that are scattered around in various web sites that exist within the internet. Furthermore, provides a search service that can easily classify positive/negative opinions and also provide searching and statistical information. Users, who want to search for opinions, can input a specific keyword to observe opinions of others easily. In addition, there is a merit in materializing the monitoring system.

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Measures of Abnormal User Activities in Online Comments Based on Cosine Similarity (코사인 유사도 기반의 인터넷 댓글 상 이상 행위 분석 방법)

  • Kim, Minjae;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.2
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    • pp.335-343
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    • 2014
  • It is more important to ensure the credibility of internet media which influence the public opinion. However, there are vague suspicions in public from the examples of manipulation of online reviews with anonymity. In this study, we explore the possibility of manipulating public opinion in online web sites. We investigate the characteristics of comments posted by users on web sites and compare each comments by using the cosine similarity function. Our result shows followings. First, we found a correlation between the similarities of comments and the article ranks in the web sites. Second, it is possible to identify abnormal user activities indicating excessive multiple posting, double posting and astroturf activities.

Domain Adaptation for Opinion Classification: A Self-Training Approach

  • Yu, Ning
    • Journal of Information Science Theory and Practice
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    • v.1 no.1
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    • pp.10-26
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    • 2013
  • Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

Implementation of reporting system for continuity of care document based on web service (Web Service 기반의 휴대용 건강 요약지 보고 시스템 구현)

  • Kim, Jong-Wook;Jeon, So-Hye;Lim, Chung-Mook;Park, Sun-Young;Kim, Nam-Hyun
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.402-404
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    • 2009
  • The development of health information technology enables people to access, view and acquire personal health record. But still, there have been a number of obstacles such as the absence of the standard to realize the ideal Personal Health Record(PHR) system. In this study, we proposed the service model that serves periodic Health Record Summary which is made by a medical specialist to people who are in the busy lives. Healthcare data from EMR in a hospital including people generate themselves at home is sent to a physician to make a medical opinion, and then it is changed into Health Level 7 Continuity of Care Document(CCD) format for interoperability. After a physician writes his opinion about patient's health condition, it will send to people by email. People who receive the health record summary data by email can save them into a USB device to view own PHR and medical comments of a physician through a computer. It will help people managing their own health condition with an opinion of a medical specialist.

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Development of Korean Opinion Analysis System using Semantic Dictionary and Inverse Opinion Processing (의미 사전과 반전 의견 처리를 이용한 한국어 의견 분석 시스템 개발)

  • Chang, Jae-Khun;Park, Jin-Soo;Ryoo, Seung-Taek
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.8
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    • pp.3070-3075
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    • 2010
  • Through Web 2.0 days, the end users express their opinions and thoughts for blogs and community spaces on the Internet. These opinions and thoughts are used to purchase products, however, users only refer to a few comments not overall opinions. Opinion Analysis System is an opinion search, developed from a natural language search, which analyzes the product's positive or negative evaluations using opinions of products and services on the Internet. In this paper, we suggest a syntactic analysis and inverse processing system that studies and processes 'Positive', 'Negative', 'Neutral' in addition to 'Inverse' information to analyze 'positive' or 'negative' for the core of sentences in Opinion Analysis Service.

A Macro Attacks Detection Model Based on Trace Back Information (트레이스 백 정보에 기반한 매크로 공격 탐지 모델)

  • Baek, Yong Jin;Hong, Suk Won;Park, Jae Heung;Kang, Gyeong Won;Kim, Sang Bok
    • Convergence Security Journal
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    • v.18 no.5_1
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    • pp.113-120
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    • 2018
  • Today, the development of information and communication technology is rapidly increasing the number of users of network-based service, and enables real-time information sharing among users on the Internet. There are various methods in the information sharing process, and information sharing based on portal service is generally used. However, the process of information sharing serves as a cause of illegal activities in order to amplify the social interest of the relevant stakeholders. Public opinion attack using macro function can distort normal public opinion, so security measures are urgent. Therefore, security measures are urgently needed. Macro attacks are generally defined as attacks in which illegal users acquire multiple IP or ID to manipulate public opinion on the content of a particular web page. In this paper, we analyze network path information based on traceback for macro attack of a specific user, and then detect multiple access of the user. This is a macro attack when the access path information for a specific web page and the user information are matched more than once. In addition, when multiple ID is accessed for a specific web page in the same region, it is not possible to distort the overall public opinion on a specific web page by analyzing the threshold count value.

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