• Journal of Environmental Impact Assessment
• /
• v.11 no.4
• /
• pp.311-319
• /
• 2002

Procedures to establish well-balanced development and effectiveness of environmental impact assessment need include various stakeholder's participation in writing and reviewing document of environmental impact assessment, collecting public opinion, and post monitoring. Accordingly, to encourage effective and efficient collection of resident's opinion analyze present conditions and problems and suggest institutional and politic alternative proposals of it. This study resulted in following conclusions. In institutional aspects, (1) Proposal for drafting document of environmental impact assessment (2) Composition of committee for collecting and regulating stakeholder's opinion (3) Width of civil participation scale. In politic aspects, (1) Use of local community (2) Guide of local information from local society and environmental specialist (3) Understandable document and data of environmental impact assessment (4) Strength of roles and duties of local government.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.243-253
• /
• 2012

An opinion mining technique which was developed from document classification in area of data mining now becomes a common interest in domestic as well as international industries. The core of opinion mining is to decide precisely whether an opinion document is a positive or negative one. Although many related approaches have been previously proposed, a classification accuracy was not satisfiable enough to applying them in practical applications. A opinion documents written in Korean are not easy to determine a polarity automatically because they often include various and ungrammatical words in expressing subjective opinions. Proposed in this paper is a new approach of classification of opinion documents, which considers only a frequency of word patterns and excludes the grammatical factors as much as possible. In proposed method, we express a document into a bag of words and then apply a learning algorithm using a frequency of word patterns, and finally decide the polarity of the document using a score function. Additionally, we also present the experiment results for evaluating the accuracy of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.5
• /
• pp.27-35
• /
• 2013

Recently, as Social Network Services(SNS) are becoming more popular, much research has been doing on analyzing public opinions from SNS. One of the most important tasks for solving such a problem is to separate opinion(subjective) documents from others(e.g. objective documents) in SNS. In this paper, we propose a new method of retrieving the opinion documents from Twitter. The reason why it is not easy to search or classify the opinion documents in Twitter is due to a lack of publicly available Twitter documents for training. To tackle the problem, at first, we build a machine-learned model for sentiment classification using the external documents similar to Twitter, and then modify the model to separate the opinion documents from Twitter. Experimental results show that proposed method can be applied successfully in opinion classification.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.117-126
• /
• 2013

Recently, as Social Network Services(SNS), such as Twitter, Facebook, are becoming more popular, much research has been doing on opinion mining. However, current related researches are mostly focused on sentiment classification or feature selection, but there were few studies about opinion document retrieval. In this paper, we propose a new retrieval method of short opinion documents. Proposed method utilizes previous sentiment classification methodology, and applies several features of documents for evaluating the quality of the opinion documents. For generating the retrieval model, we adopt Learning-to-rank technique and integrate sentiment classification model to Learning-to-rank. Experimental results show that proposed method can be applied successfully in opinion search.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.402-404
• /
• 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.

• The Journal of Society for e-Business Studies
• /
• v.19 no.2
• /
• pp.95-108
• /
• 2014

Opinion Mining is one of the application domains of text mining which extracting opinions from documents, and much researches are currently underway. Most of related researches focused on the sentiment classification which classifies the documents into positive/negative opinions. However, there is a little interest in extracting the features characterizing the individual product. In this paper, we propose the technique classifying the opinion documents according to the product features, and selecting the those features characterizing each product. In the proposed method, we utilize the document clustering technique and develope a new algorithm for evaluating the similarity between documents. In addition, through experiments, we prove the usefulness of proposed method.

• Journal of Oriental Neuropsychiatry
• /
• v.12 no.1
• /
• pp.29-45
• /
• 2001

Objectives: In order to overcome psychotherapeutic problems though the theory of oriental medicine by means of the Giungoroen(至言高論-wise saying and lofty opinion). Methods: This research was done by comparing the contents of psychotherapeutic ancient clinical document with the western medical method of psychotherapy Results: 1. Inquire into the clinical document, the psychotherapy is used treatment of wide area disease inclusive of neuropsychiatric disease different from the western medicine. 2. Inquire into the method of psychotherapy, the supportive psychotherapy and behavior therapy is applied. 3. In case of psychotherapy and treatment of medicines is done at the same time, treatment of medicines followed psychotherapy. 4. A viewpoint of Yusic(唯識-vijnaptim-atra)-a field of Buddhism, possibility of psychotherapy is showed. 5. A doctor's oriental thought and oriental medical Preservation of Health view was based. 6. The change of patient's the emotion and will is focused than disease itself. Conclusion: When western medical method of psychotherapy is complemented by a oriental thought and oriental medical Preservation of Health view, the good effects is hoped in psychotherapy.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.820-831
• /
• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.652-657
• /
• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.537-541
• /
• 2001

This study is to construct ODBC Database based Web, which has a structure of Web server and Database server connected with Database concerning server demand for the purpose of the efficient record, use and management of various document data. Each ASP OLE DB ran be saved and inferred by measuring CLC and ULC. That makes to record, use and management of document data more convenient. For the application of the suggested of the system this study is to put together into 6 categories and generalize the synthetic opinion column of high school student document.