• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.159-168
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• 1996

In this paper, the natural language dialogue understanding sytem, based on discourse information and plan recognition, is designed and implemented. The system needs to analyze the user's input utterance and acquire the discoruse information to perform plan recognition and facilitate cooperative response. This paper proposes the mehtod of controlling a dialogue, based on the algorithm for extracting the discourse information. When the discourse information for dialogue understanding is extracted, the information-based value in feature structure that is obtained form korean parser is used. And the system makes use of the structure. Thus it can offer the response that the user wants to take, and let the dialogue to study in utterance level and enhance the efficiency of dialogue understanding. In this paper, we apply the system to the hotel reservation domain and show the mehtod of using the discoruse information to control the dialogue.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.647-658
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• 2008

Customers' requirements written in a natural language are rewritten to modeling language in development phases. In many cases, those who participate in development cannot understand requirements written in modeling language. This paper proposes the translation technique from the requirement model which is written by REED(REquirement EDitor) tool into a natural language in order to help for the customer understanding requirement model. This technique consists of three phases: $1^{st}$ phase is generating the IORT(Input-Output Relation Tree), $2^{nd}$ phase is generating the RTT(Requirement Translation Tree), $3^{rd}$ phase is translating into a natural language.

• Journal of Educational Research in Mathematics
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• v.13 no.2
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• pp.123-141
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• 2003

This study investigated the understanding level and the using level of mathematical language for middle school students in terms of Freudenthal' language levels. It was proved that the understanding level task developed by current study for geometric concept had reliability and validity, and that there was the hierarchy of levels on which students understanded mathematical language. The level that students used in explaining mathematical concepts was not interrelated to the understanding level, and was different from answering the right answer according to the sorts of tasks. And, the level of mathematical language that was understood easily as students' thought, was the third level of the understanding levels. Mathematics teachers should consider the students' understanding level and using level, and give students the tasks which students could use their mathematical language confidently.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.26-47
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• 2022

Chatbots were an important research subject in the past. A chatbot is a computer program or an artificial intelligence program that participates in a conversation via auditory or textual methods. As the research on chatbots progressed, some important issues regarding them changed over time. Therefore, it is necessary to review the technology with a focus on recent advancements and core research technologies. In this paper, we introduce five different chatbot technologies: natural language processing, pattern matching, semantic web, data mining, and context-aware computer. We also introduce the latest technology for the chatbot researchers to recognize the present situation and channelize it in the right direction.

• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.161-174
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• 1992

The present discussion is concerned with showing the development of natural language processing and how it is related to information and cognition.On the basis of the computeational model,in which humans are viewed as processors of linguistic structures that use stored knowledge-grammar, lexicon and structures representing the encyclopedic information of the world,such programs of natural language understanding as Winograd's SHRDLU came out.However,such pragmatic factors as contexts and the speaker's beliefs,internts,goals and intentions are not easy to process yet.Language,ingormation and cognition are argued to be closely interrelated,and the study of them,the paper argues,can lead to the development of science on general.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.463-468
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• 1997

자연언어 대화는 사람들이 사용하는 가장 자연스러운 의사소통 수단이다. 따라서, 자연언어 대화 인터페이스를 통해서 사용자와 시스템이 편리하고 자연스러운 방법으로 의사를 교환할 수 있다. 본 논문에서는 대화 인터페이스의 필요성과 폼에 기반한 대화 인터페이스 기법에 대해서 설명한다, 폼 기반 인터페이스란 데이터베이스 검색을 위해서 질의어를 생성할 때 검색에 대한 제한 조건을 폼(form)의 형태로 나타내어, 사용자와의 대화를 통해서 폼 정보를 추출하고, 이렇게 완성된 폼을 이용하여 질의어를 생성하는 것을 말한다. 본 논문에서는 이러한 폼 기반 대화 인터페이스에서 시스템이 대화를 적절히 유도하고 사용자의 응답이나 질문에 대해 적절히 대응하기 위한 폼과 재귀적 대화 전이망(recursive dialogue transition networks)을 이용한 대화 모델에 대해 제안한다.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.426-432
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• 1999

통계적 언어 모델은 자연어 처리의 다양한 분야에서 시스템의 정확도를 높이고 수행 시간을 줄여줄 수 있는 중요한 지식원이므로 언어 모델의 성능은 자연어 처리 시스템, 특히 음성 인식 시스템의 성능에 직접적인 영향을 준다. 본 논문에서는 한국어를 위한 통계적 언어 모델을 구축하기 위한 다양한 언어 모델 실험을 제시하고 각 언어 모델들 간의 성능 비교를 통하여 통계적 언어 모델의 표준을 제시한다. 또한 형태소 및 어절 단위의 고 빈도 어휘만을 범용 언어 모델에 적용할 때의 적용률을 통하여 언어 모델 구축시 어휘 사전 크기 결정을 위한 기초적 자료를 제시한다. 본 연구는 음성 인식용 통계적 언어 모델의 성능을 판단하는 데 앞으로 큰 도움을 줄 수 있을 것이다.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.57-63
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• 2021

Spoken language understanding, which aims to understand utterance as naturally as human would, are mostly focused on English language. In this paper, we construct a Korean language dataset for spoken language understanding, which is based on a conversational corpus between reservation system and its user. The domain of conversation is limited to restaurant reservation. There are 7 types of slot tags and 5 types of intent tags in 6857 sentences. When a model proposed in English-based research is trained with our dataset, intent classification accuracy decreased a little, while slot filling F1 score decreased significantly.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1409-1425
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• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.