• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.297-303
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• 2005

When confronted with a query, question answering systems endeavor to extract the most exact answers possible by determining the answer type that fits with the key terms used in the query. However, the efficacy of such systems is limited by the fact that the terms used in a query may be in a syntactic form different to that of the same words in a document. In this paper, we present an efficient semantic query expansion methodology based on a question category concept list comprised of terms that are semantically close to terms used in a query. The semantically close terms of a term in a query may be hypernyms, synonyms, or terms in a different syntactic category. The proposed system constructs a concept list for each question type and then builds the concept list for each question category using a learning algorithm. In the question answering experiments on 42,654 Wall Street Journal documents of the TREC collection, the traditional system showed in 0.223 in MRR and the proposed system showed 0.50 superior to the traditional question answering system. The results of the present experiments suggest the promise of the proposed method.

• KIISE Transactions on Computing Practices
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• v.21 no.4
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• pp.333-337
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• 2015

In this paper, we suggest a Coreference Resolution system for Korean using Mention Pair with SVM. The system introduced in this paper, also be able to extract Mention from document which is including automatically tagged name entity information, dependency trees and POS tags. We also built a corpus, including 214 documents with Coreference tags, referencing online news and Wikipedia for training the system and testing the system's performance. The corpus had 14 documents from online news, along with 200 question-and-answer documents from Wikipedia. When we tested the system by corpus, the performance of the system was extracted by MUC-F1 55.68%, B-cube-F1 57.19%, and CEAFE-F1 61.75%.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.95-99
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• 2010

Social media refers to the content, which are created by users, such as blogs, social networks, and wikis. Recently, question-answering (QA) communities, in which users share information by questions and answers, are regarded as a kind of social media. Thus, QA communities have become a huge source of information for the past decade. However, it is hard for users to search the exact question-answer that is exactly matched with their needs as the number of question-answers increases in QA communities. This paper proposes an approach for classifying a question into three categories (information, opinion, and suggestion) according to the purpose of the question for more accurate information retrieval. Specifically, our approach is based on modified Na$\ddot{i}$ve Bayes classifier which uses structural characteristics of QA documents to improve the classification accuracy. Through our experiments, we achieved about 71.2% in classification accuracy.

• Journal of Haehwa Medicine
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• v.6 no.1
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• pp.567-584
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• 1997

Most of cancer therapy consists of surgery, chemotherapy and radiotherapy developed by modern western medicine. Often Korean patients use both modem western and oriental medicine through their cancer life. This study tried out to answer the the question : "What are the experience of a Korean cancer patients who follow oriental medicine after cancer diagnosis?" To answer to that, a micro-ethnographic research method was used. Total 6 patients were observed from March, 1996 to February, 1997. Data were obtained through interview, participant observation, audio-tape recording, field recoding, field note-taking, and ralated documents Using an analytical tool known as "pencil and scissors", the data were analyzed. First, I learned patietnts' accounts for cancer experience following oriental medicine, and I could found that they expereinced "feeling of uncertainty" through cancer life. Second, major argument was searched. : Feeling of uncertainty of cancer patients was extremely increased after cancer diagnosis. Oriental Medicine made cancer patients not only expect to improve general physical condition, but also gave them significnat emotional support to overcome their feeling of uncertanty. Third, I examined how did this argument form meanings in the context of individual life. Modem western mediacal service system could not satisfy cancer patients' informational and emotional need. But oriental medicine contribute to relieve the degree of their feeling of uncertainty. As a result of these understandings, I suggest that modern wetern medicine need to be concerned to feeling of uncertainty of cancer patietns and infomational service, and oriental medicine counsel with cancer patients much more systemically. Also nurses must improve cancer education with more accurate and practical information based on empirical data.

• The Journal of Korean Academic Society of Nursing Education
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• v.4 no.1
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• pp.107-119
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• 1998

This study tried to answer the question : 'How does the human communication happen at the oriental medicine hospital between nurse and patient?' To answer that, a micro-ethnographic research method was used. Researcher visited T university hospital of oriental medicine and observed nurse-patient communication from September 1997 to December 1997. The data was obtained through participant observation, interview, audio-tape recording, home video camera, field note-taking, and related documents. After reviewing the whole data and deliberate analysis, first, I learned that most oriental medicine nurses communicate with their patients for their routine nursing job like recording, hand-over to the next duty, report to doctor, etc. I named this type of communication as 'ritual communication'. Second, I can define major argument as follow : Human communication of oriental medicine between nurse and patient is performed more frequently and variously when nurse contacts the patient for the routine nursing activities than for the incidental activities. As a result of these understandings, I suggest that oriental nursing need to develop the body of knowledge and expand its role and independent nursing activity. Also the bureaucratic hospital management centered doctors must be changed reasonalbly.

• Journal of Digital Contents Society
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• v.11 no.3
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• pp.375-383
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• 2010

In developing question-answering (QA) systems, it is hard to analyze natural language questions syntactically and semantically and to find exact answers to given query questions. In order to avoid these difficulties, we propose a new style of question-answering system that automatically generate natural language queries and can allow to search queries fit for given keywords. The key idea behind generating natural queries is that after significant sentences within text documents are applied to the named entity recognition technique, we can generate a natural query (interrogative sentence) for each named entity (such as person, location, and time). The natural query is divided into two types: simple type and sentence structure type. With the large database of question-answer pairs, the system can easily obtain natural queries and their corresponding answers for given keywords. The most important issue is how to generate meaningful queries which can present unambiguous answers. To this end, we propose two principles to decide which declarative sentences can be the sources of natural queries and a pattern-based method for generating meaningful queries from the selected sentences.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.199-206
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• 2021

Rhetorical relations between two text fragments are essential information and support natural language processing applications such as Question - Answering (QA) system and automatic text summarization to produce an effective outcome. Question - Answering (QA) system facilitates users to retrieve a meaningful response. There is a demand for rhetorical relation based datasets to develop such a system to interpret and respond to user requests. There are a limited number of datasets for developing an Arabic QA system. Thus, there is a lack of an effective QA system in the Arabic language. Recent research works reveal that unsupervised learning can support the QA system to reply to users queries. In this study, researchers intend to develop a rhetorical relation based dataset for implementing unsupervised learning applications. A web crawler is developed to crawl Arabic content from the web. A discourse-annotated corpus is generated using the rhetorical structural theory. A Naïve Bayes based QA system is developed to evaluate the performance of datasets. The outcome shows that the performance of the QA system is improved with proposed dataset and able to answer user queries with an appropriate response. In addition, the results on fine-grained and coarse-grained relations reveal that the dataset is highly reliable.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.41-49
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• 2022

Documents often contain relative time expressions, and it is important to define a schema of the relative time information and develop a system that extracts such information from corpus. In this study, to deal with the relative time expressions, we propose seven additional attributes of timex3: year, month, day, week, hour, minute, and second. We propose a way to represent normalized values of the relative time expressions such as before, after, and count, and also design a set of rules to extract the relative time information from texts. With a new corpus constructed using the new attributes that consists of dialog, news, and history documents, we observed that our rule-set generally achieved 70% accuracy on the 1,041 documents. Especially, with the most frequently appeared attributes such as year, day, and week, we got higher accuracies compared to other attributes. The results of this study, our proposed timex3 attributes and the rule-set, will be useful in the development of services such as question-answer systems and chatbots.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.211-218
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• 2020

Recently, with the advent of blockchain technology, attempts to apply this technology to existing systems are increasing. By using the blockchain technology consensus ledger and smart contract, it is necessary to distribute certificates to various fields that require documents, attestation, authentication, verification, etc. We are studying methods using hash operation, blockchain, etc., but it is difficult to spread the technology as it has not yet reached the stage of commercialization. In this paper, user device registration authentication algorithm, blockchain-based question and answer authentication algorithm, certificate issuance, verification process and encryption algorithm, and server-side authentication for easy application in blockchain based business platform environment We proposed a blockchain-based system authentication method using four algorithms.