A Study on Human-Robot Interaction Trends Using BERTopic (BERTopic을 활용한 인간-로봇 상호작용 동향 연구)
-
- Journal of Intelligence and Information Systems
- /
- v.29 no.3
- /
- pp.185-209
- /
- 2023
With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.
본고(本稿)시리이즈의 제1보(第一報)에서 우리는 물리(物理), 사회과학(社會科學) 및 공학분야(工學分野)의 12,442명(名)의 과학자(科學者)와 기술자(技術者)에 대한 정보교환활동(情報交換活動)의 78례(例)에 있어서 일반과정(一般過程)과 몇 가지 결과(結果)를 기술(記述)한 바 있다. 4년반(年半) 이상(以上)의 기간(其間)(
The purpose of this study was to examine the job performance of dental coordinators and their perception of their job to lay the groundwork for utilizing dental personnels more efficiently. The subjects in this study were dental coordinators who worked at selected dental hospitals and clinics in Seoul, Gyeonggi province and Incheon. A survey was conducted to gather data from May 1 to August 8, 2005 and answer sheets from 108 respondents were analyzed. The findings of the study were as follows: 1. As for the length of service, 43.5 percent of the dental coordinators investigated had worked at dental institutes for five years or more, which was followed by less than two years(19.5%) and three years to less than five years(19.4%). Concerning the length of service as dental coordinators, 39.8 percent had served for less than two years, and 19.4 percent had worked for two years to less than three years and for five years or more respectively. Regarding the name of position, 38 percent were called team leaders, and 30.6 percent were called coordinators. As to duties, the largest group of them that stood at 30.6 percent were in charge of receiving, and in regard to department, the largest group, 57.4 percent, belonged to the treatment backup department. 2. Concerning education, the greatest number of them, 45.4 percent, had received education at private institutes, and 73.1 percent found it necessary for dental coordinators to take an authorized qualification test. 43.5 percent, the largest group, looked upon the central government as the best organization to authorize their qualifications and 70.8 percent believed that what they learned enabled them to perform their job successfully. As to the necessity of follow-up education as a means to improve job performance, 96.3 percent consented to it. As for the reason, 63.9 percent considered that necessary to enhance their own ability and 22.2 percent were in want of systematic education. Regarding educational expenses, 29.6 percent were subsidized by the dental institutes where they had worked and 25.9 percent had totally been responsible for that. Regarding a required course, medical service and marketing was most widely pointed out(66.7%), followed by theory and practice(65.7%) and introduction to dentistry(57.4%). As to what sort of education they wanted to receive more, dental service and marketing was selected the most, followed by practical health insurance(35.2%). 3. In regard to what type of job they performed as dental coordinators, 88.9 percent were in charge of appointment in the field of customer service, and 87.9 percent paid attention to having good manners as service providers in the area of self-management. In the field of hospital affairs, 81.3 percent were in charge of receiving. 4. As to their awareness of dental coordinator job, the largest group took pride in the job they performed (
Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.