• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.99-120
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• 2017

In order to develop a semiautomatic support system that allows researchers concerned to efficiently analyze the technical trends for the ever-growing industry and market. This paper introduces a couple of Korean sentence generation models that can automatically generate definitional statements as well as descriptions of technical terms and concepts. The proposed models are based on a deep learning model called LSTM (Long Sort-Term Memory) capable of effectively labeling textual sequences by taking into account the contextual relations of each item in the sequences. Our models take technical terms as inputs and can generate a broad range of heterogeneous textual descriptions that explain the concept of the terms. In the experiments using large-scale training collections, we confirmed that more accurate and reasonable sentences can be generated by CHAR-CNN-LSTM model that is a word-based LSTM exploiting character embeddings based on convolutional neural networks (CNN). The results of this study can be a force for developing an extension model that can generate a set of sentences covering the same subjects, and furthermore, we can implement an artificial intelligence model that automatically creates technical literature.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.215-226
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• 2020

Chatbot is emerging as an important interface window for business. This change is due to the continued development of chatbot-related research from NLP to NLU and NLG. However, the reality is that the methodological study of drawing domain knowledge and developing it into a user-friendly interactive interface is weak in the process of developing chatbot. In this paper, in order to present the process criteria of chatbot development, we applied it to the actual project based on the methodology presented in the previous paper and improved the development methodology. In conclusion, the productivity of the test phase, which is the most important step, was improved by 33.3%, and the number of iterations was reduced to 37.5%. Based on these results, the "3 Phase and 17 Tasks Development Methodology" was presented, which is expected to dramatically improve the trial and error of the chatbot development.

• Korean Journal of Ecology and Environment
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• v.36 no.1 s.102
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• pp.48-56
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• 2003

This study was evaluated about the seasonal variations of ecosystem in Nammae Reservoir based on the interrelation of physico-chemical characteristics, nutrients, chlorophyll a, b, c and standing crops of phytoplanktons. The amounts of chlorophyll a, b, c were respectively maximum (295 mg/, 9.5mg/l and 48mg/l) at station 1 in June and the standing crop of phytoplanktons was the highest ($1.7{\time}10^5$ cells/1) at stations 3 in July. The range of temperature was $7{\sim}37.4^{\circ}C$. The maxium of pH was $9.9{\sim}10.1$ at all stations in August, the minimum was 7 in September. SS was maximum (308 mg/1) at station 1 in June, while it was minimum (4 mg/l) at the same station in November. The maximal COD and DOC were 33 mg/1 and 16 mg/1 respectively at station 1 in June. As for phytoplanktons, Microcystis aeruginosa, blue-green alga in July${\sim}$August, Scenedesmus acutus, green alga in March${\sim}$May and November${\sim}$January and Cyclotella orientalis, Diatoms in October were dominant species. The amounts of P and Si were generally high in summer, they were low in autumn and winter. Nammae Reservoir assessed by trophic state index was eutrophicated and overtrophicated. These results indicated that Nammae Reservoir was faced with heavy water pollution. As preceding management for the basin of the Reservoir, it will have to be continually studied for an ecosystem reservation.

• Food Science and Preservation
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• v.15 no.3
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• pp.445-449
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• 2008

The total phenolic content and antioxidant activities of grape and fruit juice products in the Korean market were examined The total phenolic content was measured by the Folin-Ciocalteau method, and antioxidant activities were evaluated by FRAP and DPPH assays. The total phenolic content of the grape juice products were within the range $57.95{\sim}205.64\;mg/L$. Orange juice had the strongest antioxidant activity, apple juice the weakest, and grape juice was intermediate. Grape juice products exhibited a wide range of antioxidant activities. Especially, GU4, GU5, and GU9 exhibited about 80% of the DPPH radical scavenging activities, similar to the antioxidant activities by the FRAP assay. The antioxidant activities by FRAP and DPPH assays were well correlated with the total phenolic content of grape juice products (> 0.97).

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.