• Journal of Information Processing Systems
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• v.18 no.5
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• pp.614-627
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• 2022

Aspect-based sentiment analysis is to discover the sentiment polarity towards an aspect from user-generated natural language. So far, most of the methods only use the implicit position information of the aspect in the context, instead of directly utilizing the position relationship between the aspect and the sentiment terms. In fact, neighboring words of the aspect terms should be given more attention than other words in the context. This paper studies the influence of different position embedding methods on the sentimental polarities of given aspects, and proposes a position embedding interactive attention network based on a long short-term memory network. Firstly, it uses the position information of the context simultaneously in the input layer and the attention layer. Secondly, it mines the importance of different context words for the aspect with the interactive attention mechanism. Finally, it generates a valid representation of the aspect and the context for sentiment classification. The model which has been posed was evaluated on the datasets of the Semantic Evaluation 2014. Compared with other baseline models, the accuracy of our model increases by about 2% on the restaurant dataset and 1% on the laptop dataset.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.116-127
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• 2014

This paper aims to review methods for computing orthogonal projection of points onto curves and surfaces, which are given in implicit or parametric form or as point clouds. Special emphasis is place on orthogonal projection onto conics along with reviews on orthogonal projection of points onto curves and surfaces in implicit and parametric form. Except for conics, computation methods are classified into two groups based on the core approaches: iterative and subdivision based. An extension of orthogonal projection of points to orthogonal projection of curves onto surfaces is briefly explored. Next, the discussion continues toward orthogonal projection of points onto point clouds, which spawns a different branch of algorithms in the context of orthogonal projection. The paper concludes with comments on guidance for an appropriate choice of methods for various applications.

• Geomechanics and Engineering
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• v.25 no.4
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• pp.267-273
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• 2021

In this work, we compare the analytical solutions with the numerical solutions for photothermal interactions in semiconductor medium containing cylindrical cavity. This paper is devoted to a study of the photothermal interactions in semiconductor medium in the context of the coupled photo-thermal model. The basic equations are formulated in the domain of Laplace transform and the eigenvalue scheme are used to get the analytical solutions. The numerical solution is obtained by using the implicit finite difference method (IFDM). A comparison between the analytical solution and the numerical solutions are obtained. It is found that the implicit finite difference method (IFDM) is applicable, simple and efficient for such problems.

• 한국노년학
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• v.37 no.2
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• pp.475-496
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• 2017

Increasing evidence shows that ageist attitudes towards older adults develop quite early in childhood in Western culture, yet, empirical research on this topic in Korea is lacking. It has been argued that as Korea has become more youth oriented, negative views of aging have emerged and Korean children are increasingly exposured to negative stereotypes of older adults. Nuclearization of family structure and consequent reduction of intergenerational interaction is considered to be another important factor. The purpose of this study is to find out whether Korean children have ageist attitudes. Acknowledging the possibility that children tend to report in socially appropriate ways to the explicit measures of ageism, we included implicit measures of ageism. Data was collected from 570 fourth to sixth grade elementary school children selected by quota sampling. The current study used Child-Age Implicit Association Test and two other explicit measurements. The original versions were modified to be culturally applicable to the Korean context. Results indicated that when measured explicitly, children do not report preferring younger person than older person. However when measured implicitly, it was found that children at this young age already reveal negative biases toward the elderly. Contrast to the fact that the level of explicit ageism is significantly different by demographic characteristics of children, no statistical difference in the level of implicit ageism is detected. Based on the results, implications are discussed.

• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.47-60
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• 1998

The study was designed to investigate implicit and explicit memory effec representations of bilinguals. Hierarchical model of bilingual information processing word naming and translation tasks in the context of semantically categorized or rar Experiments 1 and 2, bilinguals first viewed stimulus words and performed naming or tr then implicit and explicit memory tasks. In experiment I, word recognition times(exp were significantly faster for semantic category condition than random category condi naming task and lexical decision taskOmplicit memory task)showed no difference in e experiment 2, naming task and exlicit memory task showed categorization effect but fOWE a and implcit memory task showed no categorization effect. These findings support the which posits that memory representations of bilinguals are composed of two independer a and one common conceptual store.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.179-184
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• 2021

In this study, the conversation behavior of users is investigated by using in-vehicle voice interaction system. The purpose of this study is to identify the elements of conversations that the users expect in voice interactions with systems and present the structural improvements to enable the voice interactions similar to those between people. To observe the users' behavior of voice interaction in the vehicle, the data through contextual inquiry are collected and the interview contents are analyzed by using the open coding. We have been able to explore the usefulness of voice interaction features, which are of great importance in that they increase the user's satisfaction with the features and their usage persistence. This study is meaningful in analyzing the user's empirical needs for the technology of interpersonal model from the perspective of conversation.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.108-118
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• 2010

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user's musical preferences and context and for supporting reasoning about the user's desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.157-163
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• 2014

User's sensitivity is recognized as a very important parameter for communication between company, government and personnel. Especially in many studies, researchers use voice tone, voice speed, facial expression, moving direction and speed of body, and gestures to recognize the sensitivity. Multiplex modality is more precise than single modality however it has limited recognition rate and overload of data processing according to multi-sensing also an excellent algorithm is needed to deduce the sensing value. That is as each modality has different concept and property, errors might be happened to convert the human sensibility to standard values. To deal with this matter, the sensibility expression modality is needed to be extracted using technologies like analyzing of relational network, understanding of context and digital filter from multiplex modality. In specific situation to recognize the sensibility if the priority modality and other surrounding modalities are processed to implicit values, a robust system can be composed in comparison to the consuming of computer resource. As a result of this paper, it is proposed how to assign the weight of multiplex modality using implicit data.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.39-48
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• 2017

We present penetration depth (PD) computation algorithms using explicit Minkowski sum construction ($PD_e$) and implicit Minkowski sum construction ($PD_i$). Minkowski sum construction is the most time consuming part in fast PD computation. In order to address this issue, we find a candidate solution using a centroid difference and motion coherence. Then, $PD_e$ constructs or updates partial Minkowski sum around the candidate solution. In contrast, $PD_i$ constructs only a tangent plane to the Minkowski sums iteratively. In practice, our algorithms can compute PD for complicated models consisting of thousands of triangles in a few milli-seconds. We also discuss the benefits of using different construction of Minkowski sums in the context of PD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4892-4911
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• 2015

Trust as one of important social relations has attracted much attention from researchers in the field of social network-based recommender systems. In trust network-based recommender systems, there exist normally two roles for users, truster and trustee. Most of trust-based methods generally utilize explicit links between truster and trustee to find similar neighbors for recommendation. However, there possibly exist implicit correlations between users, especially for users with the same role (truster or trustee). In this paper, we propose a novel Collaborative Filtering method called CF-TC, which exploits Trust Context to discover implicit correlation between users with the same role for recommendation. In this method, each user is first represented by the same-role users who are co-occurring with the user. Then, similarities between users with the same role are measured based on obtained user representation. Finally, two variants of our method are proposed to fuse these computed similarities into traditional collaborative filtering for rating prediction. Using two publicly available real-world Epinions and Ciao datasets, we conduct comprehensive experiments to compare the performance of our proposed method with some existing benchmark methods. The results show that CF-TC outperforms other baseline methods in terms of RMSE, MAE, and recall.