• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 2019년도 제31회 한글 및 한국어 정보처리 학술대회
• /
• pp.456-459
• /
• 2019

대화 행위는 단순한 발화 문장들의 교환을 넘어 발화자들의 다양한 주변 정보를 고려한 종합적인 판단의 결과로 볼 수 있다. 본 논문은 여섯 가지 유형의 외부 상황 정보를 기반으로 적응적 발언을 생성하는 딥러닝 기반 대화 모델을 소개한다. 직접 구축한 상황 정보들이 태깅된 대화 데이터를 바탕으로, 외부 상황 정보를 사용자 발화와 더불어 활용하는 다양한 구조의 신경망 구조를 가지는 모델과 더불어 외부 상황 정보를 사용하지 않는 모델과의 성능에 대해 비교한다. 실험 결과들은 대화 모델의 발화 생성에 있어서 상황 정보 활용의 중요성을 보여준다.

• 한국멀티미디어학회논문지
• /
• 제20권2호
• /
• pp.279-288
• /
• 2017

Nowadays, nations cyber security capabilities play an important role in a nation's defense. Security-critical infrastructures such as national defenses, public services, and financial services are now exposed to Advanced Persistent Threats (APT) and their resistance to such attacks effects the nations stability. Currently Cyber Threat Intelligence (CTI) is widely used by organizations to mitigate and deter APT for its ability to proactively protect their assets by using evidence-based knowledge. The evidence-based knowledge information can be exchanged among organizations and used by the receiving party to strengthen their cyber security management. This paper will discuss on the business process reengineering of the CTI information exchange management for a nationwide scaled control and governance by the government to better protect their national information security assets.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2023년도 춘계학술발표대회
• /
• pp.493-495
• /
• 2023

Deep learning methods and attention mechanisms have been incorporated to improve facial emotion recognition, which has recently attracted much attention. The fusion approaches have improved accuracy by combining various types of information. This research proposes a fusion network with self-attention and local attention mechanisms. It uses a multi-layer perceptron network. The network extracts distinguishing characteristics from facial images using pre-trained models on RAF-DB dataset. We outperform the other fusion methods on RAD-DB dataset with impressive results.

• 한국정보기술학회 영문논문지
• /
• 제10권1호
• /
• pp.45-56
• /
• 2020

Despite extensive research, performance enhancement of keyphrase (KP) extraction remains a challenging problem in modern informatics. Recently, deep learning-based supervised approaches have exhibited state-of-the-art accuracies with respect to this problem, and several of the previously proposed methods utilize Bidirectional Encoder Representations from Transformers (BERT)-based language models. However, few studies have investigated the effective application of BERT-based fine-tuning techniques to the problem of KP extraction. In this paper, we consider the aforementioned problem in the context of scientific articles by investigating the fine-tuning characteristics of two distinct BERT models - BERT (i.e., base BERT model by Google) and SciBERT (i.e., a BERT model trained on scientific text). Three different datasets (WWW, KDD, and Inspec) comprising data obtained from the computer science domain are used to compare the results obtained by fine-tuning BERT and SciBERT in terms of KP extraction.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2020년도 추계학술발표대회
• /
• pp.818-821
• /
• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
• /
• pp.239-244
• /
• 2023

신경망 기반의 다국어 및 교차 언어 정보 검색 모델은 타겟 언어로 된 학습 데이터가 필요하지만, 이는 고자원 언어에 치중되어있다. 본 논문에서는 이를 해결하기 위해 영어 학습 데이터와 한국어-영어 병렬 말뭉치만을 이용한 효과적인 다국어 정보 검색 모델 학습 방법을 제안한다. 언어 예측 태스크와 경사 반전 계층을 활용하여 인코더가 언어에 구애 받지 않는 벡터 표현을 생성하도록 학습 방법을 고안하였고, 이를 한국어가 포함된 다국어 정보 검색 벤치마크에 대해 실험하였다. 본 실험 결과 제안 방법이 다국어 사전학습 모델과 영어 데이터만을 이용한 베이스라인보다 높은 성능을 보임을 실험적으로 확인하였다. 또한 교차 언어 정보 검색 실험을 통해 현재 검색 모델이 언어 편향성을 가지고 있으며, 성능에 직접적인 영향을 미치는 것을 보였다.

• 한국IT서비스학회지
• /
• 제12권3호
• /
• pp.127-149
• /
• 2013

Is the social web environment in which production, distribution and consumption of information occurs from users an environment where manifestation of collective intelligence is easily made? Or is the social web environment a condition that incites people to depend on the groupthink due to biased information? It is important to conduct empirical studies on the possibility of social media as a tool of collective intelligence under the situation where conflicting opinions prevail. However, most of the existing studies related to this were limited to an exploratory research rather than an empirical research. In this regard, this study attempted to examine if the social media can perform a part as a platform of the collective intelligence empirically. Based on the experimental results, it can be safely said that the communication methods of social media showed its usefulness in both 'intellectual capacity of the group' and 'problem-solving skill of the group.'

• 한국IT서비스학회지
• /
• 제18권1호
• /
• pp.201-217
• /
• 2019

Cars have become a necessity in modern life. It is widely used to transport people or products to a destination conveniently. However, the addition of a navigation service that provides route information and more makes driving more convenient and safer. Recent developments in the mobile app ecosystem encourages people to adopt not only an installation-type car navigation, but also a mobile app navigation, supporting connected car concepts. It should be noted that mobile apps with mobile Internet can be a significant linkage between information acquired online and offline business. This study demonstrates the impact of the app use experience for a driver in the context of applying artificial intelligence service. As a result, the introduction of artificial intelligence services has a statistically significant moderating effect on the use of mobile navigation apps. This seminal research is valuable as it evaluates the role of artificial intelligence applied to mobile navigation apps.

• 한국멀티미디어학회논문지
• /
• 제25권10호
• /
• pp.1512-1523
• /
• 2022

Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2022년도 춘계학술대회
• /
• pp.177-179
• /
• 2022

Google Deepmind Challenge match에서, Alphago가 바둑 대결에서 4승1패로 한국의 이세돌(인간)에 승리하였다. 드디어, 인공지능은 인간 지능의 활용을 넘어서고 있는 것이다. 한국 정부의 디지털뉴딜의 사업예산은 2022년 9조원이며, 인공지능 학습용 data 구축사업은 301종을 추가로 확보한다. 2023년부터는 산업의 전 분야에서 인공지능의 학습의 활용과 적용으로 산업 패러다임이 변화될 것이다. 본 논문은 인공지능 알고리즘을 활용하기 위한 연구를 한다. 인공지능 학습에서 data의 분석과 판단을 중심으로, 인공지능 머신러닝과 딥러닝 학습에서의 알고리즘의 적절한 활용 대상과 활용 범위에 대한 연구를 한다. 본 연구는 4차산업혁명기술의 인공지능과 5차산업혁명기술의 인공지능로봇 활용의 기초자료를 제공할 것이다.