• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.635-648
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• 2019

Many studies of entrepreneurship have focused on positive characteristics such as self-efficacy and self-leadership. However, recent studies are being conducted to find out effects of negative characteristics on entrepreneurship, such as ADHD-like behavior. This study investigated the impact of ADHD-like behavior on Entrepreneurial Orientation(EO) and Entrepreneurial Intention(EI). In addition, this study investigated the impact of schema related to opportunity recognition and entrepreneurial alertness on EO and EI. Data were collected from youth generation in Korea through online survey. The results show that the ADHD isn't significant for both risk-taking and innovativeness, but it has negative impact on pro-activeness. On the other hand, Schema has positive impact on all EO and EO has positive impact on EI. As a results, The higher ADHD-like behavior, the lower pro-activeness. Therefore ADHD-like behavior could lower EI through pro-activeness. However, Schema has positive impact on all EO, which has positive impact on EI.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.2
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• pp.245-261
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• 2019

The purpose of this study was to investigate factors affecting the use of modern photographic records. Data was collected through a survey of 95 potential users for photographic records in future. Independent variables in this study included evidential value, informational value, usage value, intrinsic value. Dependent variable was selected as use intention for photographic records. The results of analysis of multi-regression analysis showed that evidential value and intrinsic value were found to have a positive impact on use intention for photographic records in modern korea. The results from this study can be used as important basic data for building archives for photographic record or for developing the policy for effective photographic records management.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.75-84
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• 2018

This study analyzed users' acceptance and intention to use in addition to needs and preferences of smart home technologies, and identified the differences in technology preference and acceptance by different factors. The subjects were residents in the 40s and 60s residing in the Seoul or suburbs of Seoul, and questionnaires were conducted in the 40s while interviews with questionnaires were conducted in the 60s. A total of 105 questionnaires were used as data, and frequency, mean, crossover, independent sample t test, one-way ANOVA and multiple regression analysis were performaed using SPSS23. The results of this study are as follows. First, hypertension, hyperlipidemia and hypercholesterolemia were the most common diseases among respondents and if there was no discomfort, they would like to continue living in the homes of the current residence. Therefore, the direction of smart home development should support the daily living and health care so that residents can live a healthy life for a long time in their living space. Second, the technologies that residents most need were a control technology of residential environments and a monitoring technology of residents' health and physiological changes. The most preferred sensor types are motion sensors and speech recognition while video cameras have a very low preference. Third, technology anxiety was the most significant factor influencing intention to accept smart home technology. The greater the technology anxiety is, the weaker the acceptance of technology. Fourth, when applying smart residential technology in homes, various resident characteristics should be considered. Age and technology intimacy were the most influential variables, and accordingly there were differences in technology preference and acceptance. Therefore, a user-friendly smart home plan should be done in the consideration of the results.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.5-14
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• 2019

Starting with the market vitalization project in 2008, The Gwangju Dae-in Art Market has attracted to many artists, changing into cultural and art market. After the project was carried out for a certain period of time, a study was conducted to determine the differing opinions of the artists and merchants in regards to the market. The study also examined and analyzed the factors affecting the artists' continuous activities. The difference in recognition perception between artists and merchants was analyzed through a T-test. PLS-regression analysis was used for the artists' continuing intention to work. As a result, the artists and merchants recognized that the number of visitors increased after the influx of artists. Programs that had a positive impact on the artist's intention for sustainable activities were as follows: the 'Art Products Creation Workshop', where artists, merchants, and citizens collaborate to develop commodities needed for the market; 'Hanpyeong Gallery', where artists directly or indirectly interact with merchants and citizens; the 'Artist-Merchant Workshop', where artists and merchants produce articles required for the market; 'C'est Si Bon', which expresses the placeness of the market into art; and the 'Dae-in Art Night Market', where citizens, merchants and visitors can sell their own works. On the other hand, programs with the negative effect were those where artists' participation was low or none, as the policy implications, they should be actively develop this type of programs, where artists could participate and interact with citizens and merchants, like this visitors and sales can be increased.

• Smart Media Journal
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• v.11 no.3
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• pp.90-101
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• 2022

Buses are a popular means of transportation. As such, thorough preparation is needed for passenger safety management. However, the safety system is insufficient because there are accidents such as a death accident occurred when the bus departed without recognizing the elderly approaching to get on in 2018. There is a safety system that prevents pinching accidents through sensors on the back door stairs, but such a system does not prevent accidents that occur in the process of getting on and off like the above accident. If it is possible to predict the intention of bus passengers to get on and off, it will help to develop a safety system to prevent such accidents. However, studies predicting the intention of passengers to get on and off are insufficient. Therefore, in this paper, we propose a 1×1 CNN3D-based getting on and off intention prediction model using skeleton keypoints of passengers extracted from the camera image attached to the bus through UDP-Pose. The proposed model shows approximately 1~2% higher accuracy than the RNN and LSTM models in predicting passenger's getting on and off intentions.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.37-48
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• 2022

This research is an empirical research of Chinese OTT Audiences on the effects of advertising model attributes on consumers' advertising perception, purchase intention, Flow and addiction. Recently, as the cosmetics market in China has grown, the role of advertising models has been highlighted, and shopping addiction caused by excessive Flow is becoming a social problem. Researchers set up a research model and tried to test which characteristics of the advertising model lead consumers to purchase, Flow and ultimately lead to addiction. Results are as follows. It was confirmed that advertisement model attributes such as recognition and attractiveness had a positive effect on viewers' advertising perception and attitude, and viewers' perceived usefulness had a positive effect on purchase intention and Flow. In addition, the purchase intention of the viewers had a positive effect on the addiction to cosmetics.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.

• Journal of the HCI Society of Korea
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• v.10 no.2
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• pp.21-26
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• 2015

NUI (Natural User Interface) system interprets the user's natural movement or the signals from human body to the machine. sEMG (surface electromyogram) can be observed when there is any effort in muscle even without actual movement, which is impossible with camera and accelerometer based NUI system. In sEMG based movement recognition system, the minimal number of electrodes is preferred to minimize the inconvenience. We analyzed the decrease in recognition accuracy as decreasing the number of electrodes. For the four kinds of movement intention without movement, extension (up), flexion (down), abduction (right), and adduction (left), the multilayer perceptron classifier was used with the features of RMS (Root Mean Square) from sEMG. The classification accuracy was 91.9% in four channels, 87.0% in three channels, and 78.9% in two channels. To increase the accuracy in two channels of sEMG, RMSs from previous time epoch (50-200 ms) were used in addition. With the RMSs from 150 ms, the accuracy was increased from 78.9% to 83.6%. The decrease in accuracy with minimal number of electrodes could be compensated partly by utilizing more features in previous RMSs.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.1-25
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• 2008

Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between the user's intention and the system's understanding, which eventually results in a misinterpretation. To fill in the gap, people in human-to-human dialogs try to clarify the major causes of the misunderstanding to selectively correct them. This paper presents a method of clarification techniques to human-to-machine spoken dialog systems. We viewed the clarification dialog as a two-step problem-Belief confirmation and Clarification strategy establishment. To confirm the belief, we organized the clarification process into three systematic phases. In the belief confirmation phase, we consider the overall dialog system's processes including speech recognition, language understanding and semantic slot and value pairs for clarification dialog management. A clarification expert is developed for establishing clarification dialog strategy. In addition, we proposed a new design of plugging clarification dialog module in a given expert based dialog system. The experiment results demonstrate that the error verifiers effectively catch the word and utterance-level semantic errors and the clarification experts actually increase the dialog success rate and the dialog efficiency.