• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1407-1423
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• 2020

A graph is a data structure consisting of nodes and edges between these nodes. Graph embedding is to generate a low dimensional vector for a given graph that best represents the characteristics of the graph. Recently, there have been studies on graph embedding, especially using deep learning techniques. However, until now, most deep learning-based graph embedding techniques have focused on unweighted graphs. Therefore, in this paper, we propose a graph embedding technique for weighted graphs based on long short-term memory (LSTM) autoencoders. Given weighted graphs, we traverse each graph to extract node-weight sequences from the graph. Each node-weight sequence represents a path in the graph consisting of nodes and the weights between these nodes. We then train an LSTM autoencoder on the extracted node-weight sequences and encode each nodeweight sequence into a fixed-length vector using the trained LSTM autoencoder. Finally, for each graph, we collect the encoding vectors obtained from the graph and combine them to generate the final embedding vector for the graph. These embedding vectors can be used to classify weighted graphs or to search for similar weighted graphs. The experiments on synthetic and real datasets show that the proposed method is effective in measuring the similarity between weighted graphs.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.27-33
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• 2022

In this paper, we propose a novel generator architecture for multi-domain style transfer method not an image to image translation, as a method of generating a styled image by transfering a style to the content image. A latent vector and Gaussian noises are added to the generator of GAN so that a high quality image is generated while considering the characteristics of various data distributions for each domain and preserving the features of the content data. With the generator architecture of the proposed GAN, networks are configured and presented so that the content image can learn the styles for each domain well, and it is applied to the domain composed of images of the four seasons to show the high resolution style transfer results.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.17-24
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• 2009

Increasing use of information system has led to larger amount of developing expenses and demands on software. Until recent days, the model using regression analysis based on statistical algorithm has been used. However, Machine learning is more investigated now. This paper estimates the software cost using SVR(Support Vector Regression). a sort of machine learning technique. Also, it finds the best set of parameters applying immune algorithm. In this paper, software cost estimation is performed by SVR based on immune algorithm while changing populations, memory cells, and number of allele. Finally, this paper analyzes and compares the result with existing other machine learning methods.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.209-216
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. This paper presents a software cost estimation method using a support vector machine. Support vector machine is one of the efficient techniques for classification, and it is the classification method of input data based on Maximum-Margin Hyperplane. But SVM has the problem of the selection of optimal parameters, because it is dependent on user's parameters. This paper selects optimized SVM parameters using advanced method, and estimates software development cost. The proposed approach outperform some recent results reported in the literature.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.369-372
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• 2022

본 논문에서는 장애물 객체의 회전 벡터를 이용하여 VR 환경에서의 효율적으로 음향 처리 및 합성하는 방법을 제안한다. 현실에서 소리와 장애물이 있을 때, 소리는 장애물의 형태에 따라 퍼지면서 전파되는 형태를 보여준다. 이 같은 특징을 가상현실 환경에 유사하게 음향 처리하고자 하며 이를 위해 장애물 객체의 위치와 소리의 근원지 위치를 입력으로 소리의 전파 형태를 근사한다. 이때 모서리 부근에서 표현되는 소리의 회전을 계산하기 위해 장애물의 회전벡터(Curl vector)를 기반으로 소리의 회전을 추출하였으며, 장애물 형태를 컨볼루션(Convolution)하여 소리가 바깥 방향으로 전파되는 형태를 모델링한다. 또한, 장애물과 소리 벡터 사이의 거리, 소리 근원지와 소리 벡터 사이의 거리를 계산하여 소리의 크기를 감쇠 시켜 주며, 최종적으로 장애물 주변으로 퍼지는 벡터 모양인 외부벡터를 합성하여 장애물로부터 외부로 퍼지는 벡터의 방향을 설정한다. 본 논문에서 제안하는 방법을 이용한 소리는 장애물과의 거리와 형태를 고려하여 퍼지는 사운드 벡터 형태를 보여주며, 소리 위치에 따라 소리 감소 패턴이 변경되고, 장애물 모양에 따라 흐름이 조절되는 결과를 보여준다. 이 같은 실험은 실제 현실에서 소리가 장애물의 모양에 따라 나타나는 소리의 변화 및 패턴을 거의 유사하게 표현할 수 있다.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.77-86
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• 1996

In this paper we deal with the problem of recovering 3-D motion and structure from a time-varying 2-D velocity vector field. A great deal has been done on this topic, most of which has concentrated on finding necessary and sufficient conditions for there to be a unique 3-D solution corresponding to a given 2-D motion. While previous work provides useful theoretical insight, in most situations the known algorithms have turned out to be too sensitive to be of much practical use. It appears that any robust algorithm must improve the 3-D solutions over time. As a step toward such algorithm, we present a method for recovering 3-D motion and structure from a given time-varying 2-D velocity vector field. The surface of the object in the scene is assumed to be locally planar. It is also assumed that 3-D velocity vectors are piecewise constant over three consecutive frames (or two snapshots of flow field). Our formulation relates 3-D motion and object geometry with the optical flow vector as well as its spatial and temporal derivatives. The linearization parameters, or equivalently, the first-order flow approximation (in space and time) is sufficient to recover rigid body motion and local surface structure from the local instantaneous flow field. We also demonstrate, through a sensitivity analysis carried out for synthetic and natural motions in space, that 3-D motion can be recovered reliably.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.41-49
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• 2024

This paper proposes dual symbol superposition block carrier transmission with frequency domain equalization (DSS-FDE) system. This system is based upon χ-transform matrix, which is obtained by concatenation of discrete Hartley transform (DHT) matrix and discrete Fourier transform (DFT) matrices into single matrix that is remarkably sparse, so that, as it will be shown in this paper, it only has non-zero entries on its principal diagonal and one below the principle anti-diagonal, giving it shape of Latin alphabet χ. When multiplied with constellation mapped complex transmit vector, each entry of resultant vector is weighted superposition of only two entries of original vector, as opposed to all entries in conventional DFT based OFDM. Such a transmitter is close to single carrier block transmission with frequency domain equalization (SC-FDE), which is known to have no superposition. The DSS-FDE offers remarkable simplicity in transmitter design and yields great benefits in reduced complexity and low PAPR. At receiver-end, it offers the ability to harvest full diversity from multipath fading channel, full coding gain, with significant bit error rate (BER) improvement. These results will be demonstrated using both analytical expressions, as well as simulation results. As will be seen, this paper is Part III of three-paper series on alternative transforms for multicarrier communication (MC) systems.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.164-166
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• 2012

최근 스마트 기기의 보급과 무선 인터넷망의 보급으로 언제 어디에서나 비디오를 시청할 수 있다. 하지만 무선 인터넷 망의 품질이 안좋을 경우 영상의 QoS(Quality of Service)를 낮춰 프레임을 스킵하여 전송하게 된다. 이 때 FRUC(Frame Rate Up Conversion)기술을 적용한다면 원본의 프레임 레이트를 확보할 수 있어 QoS를 높일 것으로 기대한다. FRUC에서 MV(Motion Vector)추정시에 연산량이 매우 높아서 스마트 기기에 적용하는 것이 어렵지만 H.264코덱으로 인코딩된 동영상은 자체적으로 MV정보를 갖고 있기 때문에 이 MV를 FRUC에 적용할 수 있다면 FRUC의 연산량을 줄일 수 있을 것이다. 이를 위해서 H.264에 적용된 ME(Motion Estimation)와 FRUC에 적용된 ME의 차이를 고려하여 H.264코덱의 MV가 유용한지 분석하는 것이 선행돼야 한다. 본 논문에서는 H.264 MV와 FRUC의 MV의 차이를 분석하고 유용성을 판단하는 실험을 통해 H.264로 인코딩 된 비디오의 MV중 상당수가 FRUC에 적합함을 확인했다.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.373-378
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• 2005

Computer-Mediated Communication (CMC) based on electronic bulletin board system (e-BBS) has been widely used for various educational purposes since the advent of the Internet. Instructors can achieve pedagogical goals by analyzing the contents of postings. They can be benefited technically from analytic information on discussion activities. Studies on content analysis and social presence in communication have been traditionally done by social studies. However, researches on computational and logical analysis of the phenomenon are rare. To do that we propose a formal model to represent and analyze communication activities logically. The model consists of interactivity vector providing a formal representation of discussion activities and interactivity chart providing a graphical representation of interactivity vector. The formal approach can be used as a useful technical assistance to analyze and compare discussion groups computationally.