• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.434-438
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• 1994

자연어 생성 시스템은 기계 변역이나 대화 시스템 등 여러 시스템의 인터페이스로 중요한 역할을 한다. 자연어 생성 시스템을 효율적으로 구축하고, 확장을 용이하게 하기 위해서는 해당언어의 생성에 필요한 정보를 효과적으로 표현할 수 있는 규칙 표현법이 필요하다. 본 논문은 한국어 생성에서 사용하는 격틀과 격틀 이외의 여러 정보를 표현할 수 있는 표현법을 제안하였다. 그리고 제안한 규칙을 수행하기 위해서 Shieber의 semantic-head-driven-generation방식[4]을 변형한 엔진을 구현하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.240-244
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• 2010

본 논문에서는 단백질 간 상호작용 자동 식별을 위해서 구문 트리 커널을 확장한 시맨틱 구문 트리 커널을 제안한다. 기존의 구문 트리 커널은 구문 트리의 단말 노드를 구성하는 개별 어휘에 대해서 단순하게 외형적 비교를 수행하기 때문에 실제 의미적으로는 유사한 두 구문 트리의 커널 수치가 상대적으로 낮아져서 단백질 간 상호작용 식별의 성능이 떨어지는 문제점이 발생한다. 이를 극복하기 위해서 두 구문 트리의 구문적 유사도(syntactic similarity)와 어휘 의미적 유사도(lexical semantic similarity)를 동시에 효과적으로 계산하여 이를 결합하는 새로운 커널을 고안하였다. 그리고 제안된 시맨틱 구문 트리 커널을 활용하여 단백질 간 상호작용 식별 성능을 향상시킬 수 있음을 실험을 통하여 보여주었다.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.93-96
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• 2003

The present study was conducted to investigate the difference of cortical activation in naming the picture in Korean and English. Experimental design was 2(Korean, English) language condition x 4(no distractor, semantic related distractor, semantic unrelated distrator, corresponding distractor) distractor condition. language condition was between subject factor and distractor condition was within subject factor. The result was that Korean naming condition showed less cortical activation than English naming condition. The activation region was reported in each condition.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.502-508
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• 2008

With the increased use of the internet and the tremendous amount of data it transfers, it is more necessary to summarize documents. We propose a new method using the Non-negative Semantic Variable Matrix (NSVM) and the generic important of semantic features obtained by Non-negative Matrix Factorization (NMF) to extract the sentences for automatic generic summarization. The proposed method use non-negative constraints which is more similar to the human's cognition process. As a result, the proposed method selects more meaningful sentences for summarization than the unsupervised method used the Latent Semantic Analysis (LSA) or clustering methods. The experimental results show that the proposed method archives better performance than other methods.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.23-28
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• 2002

A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.180-182
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• 2007

The present study was carried out to investigate how two languages are represented and processed for the late Korean-English bilinguals. To this end, we compared the naming times of Korean-English bilinguals on a series of the picture-word interference tasks. The entire experiment is divided into four parts, each of which required participants to name the pictures in Korean or in English with distractor words visually presented either in Korean or English. The distractor words were semantically related or unrelated to the picture. The results showed that, in different language conditions (L1 naming-L2 distractor, L2 naming - L1 distractor), there was only numerical difference between semantic related and unrelated condition. In same language conditions (L1 naming-L1 distractor, L2 naming-L2 distractor), however, significant semantic interference effect occurred. And, the interference effect was stronger in the L1 distractor condition than in the L2 distractor condition. These results suggest that the semantic processing of L1 and L2 for the late bilinguals are independent each other.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.37-51
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• 2017

There has been a growing concern on ontology especially in recent knowledge-based industry and defining a field-customized semantic word network is essential for building it. In this paper, a word network for ontology is established with 785 publications of Korean Society of Rural Planning(KSRP), from 1995 to 2017. Semantic relationships between words in the publications were quantitatively measured with the 'normalized pointwise mutual information' based on the information theory. Appearance and co-appearance frequencies of nouns and adjectives in phrases are analyzed based on the assumption that a 'noun phrase' represents a single 'concept'. The word network of KSRP was compared with that of $WordNet^{TM}$, a world-wide thesaurus network, for the verification. It is proved that the KSRP's word network, established in this paper, provides words' semantic relationships based on the common concepts of Korean rural planning research field. With the results, it is expecting that the established word network can present more opportunity for preparation of the fourth industrial revolution to the field of the Korean rural planning.

• Speech Sciences
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• v.13 no.4
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• pp.187-200
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• 2006

The speech synthesis technology is widely used and its application area is also being broadened to an automatic response service, a learning system for handicapped person, etc. However, the sound quality of the speech synthesizer has not yet reached to the satisfactory level of users. To make a synthesized speech, the existing synthesizer generates rhythms only by the interval information such as space and comma or by several punctuation marks such as a question mark and an exclamation mark so that it is not easy to generate natural rhythms of people even though it is based on mass speech database. To make up for the problem, there is a way to select rhythms after processing language from a higher level information. This paper proposes a method for generating tags for controling rhythms by analyzing the meaning of sentence with speech situation information. We use the Systemic Functional Grammar (SFG) [4] which analyzes the meaning of sentence with speech situation information considering the sentence prior to the given one, the situation of a conversation, the relationship among people in the conversation, etc. In this study, we generate Semantic Speech Control Tag (SSCT) by the result of SFG's meaning analysis and the voice wave analysis.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.81-89
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• 2011

It is presumable that properly designed earcons given simultaneously with visual information could enhance the situation awareness of operators when they are involving in highly complicate process control activities. In this study, population stereotypes of earcons with respect to process control information were identified using 60 Korean subjects. To do this, 11 most distinctive earcons were selected from various earcons having different pitch, rhythm, and timbre. Associations between the selected earcons and 40 pairs of adjectives used to describe the state of control in process were gathered from 37 subjects using a semantic differential method. Based on the results from multivariate analyses, the 40 pairs of adjectives were aggregated into three distinctive semantic dimensions. The emotional maps of the 11 earcons matched with the semantic dimensions were presented in this study. On the basis of these results, a general guideline was suggested for designing earcons to deliver process control information.