제품관여 수준에 따라 소셜 정보가 추천 성능에 미치는 영향

송희석(Hee Seok Song),주석정(Seok Jeong Joo),이재훈(Jae Hoon Lee) 한국데이타베이스학회 2014 Journal of information technology applications & m Vol.21 No.4

사회네트워크에서 사용자 행위정보를 활용한 퍼지 기반의 신뢰관계망 추론 모형

송희석(Hee Seok Song) 한국데이타베이스학회 2010 Journal of information technology applications & m Vol.17 No.4

We are sometimes interacting with people who we know nothing and facing with the difficult task of making decisions involving risk in social network. To reduce risk, the topic of building Web of trust is receiving considerable attention in social network. The easiest approach to build Web of trust will be to ask users to represent level of trust explicitly toward another users. However, there exists sparsity issue in Web of trust which is represented explicitly by users as well as it is difficult to urge users to express their level of trustworthiness. We propose a fuzzy-based inference model for Web of trust using user behavior information in social network. According to the experiment result which is applied in Epinions.com. the proposed model show improved connectivity in resulting Web of trust as well as reduced prediction error of trustworthiness compared to existing computational model.

소셜네트워크에서 신뢰의 전이성과 결합성에 관한 연구

송희석(Hee Seok Song) 한국데이타베이스학회 2011 Journal of information technology applications & m Vol.18 No.4

Trust prediction between users in social network based on the trust propagation assumes properties of transitivity and composability of trust propagation. But it has been hard to find studies which test on how those properties have been operated in real social network. This study aims to validate if the longer the distance of trust paths and the less the numbers of trust paths, the higher prediction error occurs using two real social network data set. As a result, the longer the distance of trust paths, we can find higher prediction error when predicting level of trust between source and target users. But we can not find decreasing trend of prediction error though the possible number of trust paths between source and target users increases.

인과지도에 기반한 미래 주파수공유 생태계 분석

송희석(Hee Seok Song),김태한(Taehan Kim) 한국데이타베이스학회 2013 Journal of information technology applications & m Vol.20 No.4

There is tremendous increasing demand on spectrum resource which is boosted by spread of cloud computing and M2M telecommunication as well as smart phone and tablet PC. Recently, spectrum sharing technology has drawn attention to the spectrum policy makers as a promising way to overcome limitation of scarce spectrum resource. To succeed in commercialization of spectrum sharing technology, it is necessary to prospect the future business ecosystem of spectrum sharing and develop appropriate policies and laws at the same time along with the advance of spectrum sharing technology. The purpose of this paper is to prospect future spectrum sharing ecosystem and analyze business ecosystem of spectrum sharing with casual loop map. With the causal map and system dynamics method, it is possible to analyze feedback loops which is not limited to linear thinking and build policies which optimize positive dynamics in business ecosystem of spectrum sharing.

페이스북 사용자간 내재된 신뢰수준 예측 방법

송희석(Hee Seok Song) 한국데이타베이스학회 2013 Journal of information technology applications & m Vol.20 No.2

Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore, it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method, we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

인과지도에 기반한 주파수공유 생태계 활성화 정책 설계

송희석(Hee Seok Song),김재경(Jae Kyung Kim),김태한(Tae han Kim) 한국IT서비스학회 2014 한국IT서비스학회지 Vol.13 No.4

Demand of spectrum resource is tremendously increasing recently and this trend will continues in the future due to the wide spread of IT services based on cloud computing and Internet of Things technology and as well as smart devices. Recently, spectrum sharing technology has drawn attention to the spectrum policy makers as a promising way to overcome the shortage problem of scarce spectrum resource. To succeed in commercialization of spectrum sharing technology, it is necessary to prospect the future business ecosystem of spectrum sharing and develop appropriate policies and laws at the same time along with the advance of spectrum sharing technology. The purpose of this paper is to analyze casual relationships between enablers in future business ecosystem of spectrum sharing and propose policies to vitalize spectrum sharing ecosystem based on a system dynamics causal map proposed in the previous research. With the causal map and system dynamics method, it is possible to analyze feedback loops exist in the business ecosystem of spectrum sharing and build policies which optimize positive dynamics in business ecosystem of spectrum sharing. As a result, policy leverages were found in four areas; spectrum supply, spectrum demand, spectrum quality and technology, and spectrum transaction cost. For those policy leverages, 13 policies were identified and intervention timing for each policy was discussed. Finally, the promotion policies of government and market participants to vitalize spectrum sharing ecosystem were discussed.

ANFIS에서 생성된 규칙의 해석용이성 평가

송희석(Hee Seok Song),김재경(Jae Kyeong Kim) 한국지능정보시스템학회 2009 지능정보연구 Vol.15 No.4

퍼지신경망 모형은 인공신경망의 네트워크 구조 표현방법 및 학습알고리듬과 퍼지시스템의 추론방법을 통합한 모형으로 제어 및 예측분야에 성공적으로 적용되고 있다. 본 연구에서는 퍼지신경망 모형 중 우수한 예측정확도로 인해 최근 각광받고 있는 ANFIS (Adaptive Network-based Fuzzy Inference System)모형에서 생성된 퍼지규칙의 해석용이성을 평가하였다. ANFIS모형은 인간 전문가와 상호작용하면서 규칙을 정제해 나갈 수 있다. 특히 인간전문가의 사전지식을 이용하여 초기 퍼지규칙을 만들고 난 후 모형을 학습하면 최적에 수렴하는 시간을 단축할 뿐 아니라, 전역 최적치 도달가능성이 높아진다고 보고되고 있다. 이러한 관점에서 볼 때 규칙의 해석용이성은 인간 전문가와의 상호작용을 위해 매우 중요한 이슈가 될 수 있다. 본 연구에서는 ANFIS모형과 의사결정나무 모형에서 생성된 규칙을 해석용이성 관점에서 비교하기 위한 측도를 제안하고 각 규칙들을 비교하였다. 본 연구에서 제안된 해석용이성 측도들은 규칙을 생성하는 다양한 기계학습 모형의 규칙생성 능력을 평가하는 기준으로도 활용될 수 있을 것이다. Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of outstanding performance of control and forecasting accuracy. ANFIS has capability to refine its fuzzy rules interactively with human expert. In particular, when we use initial rule structure for machine learning which is generated from human expert, it is highly probable to reach global optimum solution as well as shorten time to convergence. We propose metrics to evaluate interpretability of generated rules as a means of acquiring domain knowledge and compare level of interpretability of ANFIS fuzzy rules to those of C5.0 classification rules. The proposed metrics also can be used to evaluate capability of rule generation for the various machine learning methods.

시스템 다이내믹스를 이용한주파수 공유 생태계 활성화 정책대안 비교 분석 연구

송희석(Hee Seok Song),김재경(Jae Kyung Kim),김태한(Taehan Kim) 한국데이타베이스학회 2014 Journal of information technology applications & m Vol.21 No.4

ANFIS 기반 분류모형의 설계 및 성능평가

송희석(Hee Seok Song),김재경(Jae Kyeong Kim) 한국지능정보시스템학회 2009 지능정보연구 Vol.15 No.3

퍼지신경망 모형은 인공신경망의 네트워크 구조 표현방법 및 학습알고리듬과 퍼지시스템의 추론방법을 통합한 모형으로 제어 및 예측분야에 성공적으로 적용되고 있다. 본 연구에서는 퍼지신경망 모형 중 우수한 예측정확도로 인해 최근 각광받고 있는 ANFIS (Adaptive Network-based Fuzzy Inference System)모형을 기반으로 하는 분류모형을 설계하고 기존의 분류기법(C5.0 의사결정나무)과 비교하여 분류 정확성 관점에서 평가한다. ANFIS 추론의 경우, 최종 결과값이 계급값이 아닌 연속형 변수값을 취하게 되므로 산출된 결과값을 이용하여 적절한 계급값을 할당하는 과정이 필요하다. 본 연구에서는 의사결정나무기법을 이용하여 계급값을 할당하는 방식과 군집분석을 이용하여 계급값을 할당하는 두 가지 방식을 제안하고 두 가지 데이터 세트에 적용하여 ANFIS를 기반으로 한 분류모형의 정확도를 평가하였다. Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of its outstanding accuracy of control and forecasting area. We design a new classification model based on ANFIS and evaluate it in terms of classification accuracy. We identified ANFIS-based classification model has higher classification accuracy compared to existing classification model, C5.0 decision tree model by comparing their experimental results.

유·무선인터넷 서비스의 경쟁관계 분석

송희석(Hee Seok Song),여재현(Jaehyun Yeo) 대한전자공학회 2004 대한전자공학회 학술대회 Vol.2004 No.12