• Title/Summary/Keyword: Frequency based Text Analysis

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Proposal for User-Product Attributes to Enhance Chatbot-Based Personalized Fashion Recommendation Service (챗봇 기반의 개인화 패션 추천 서비스 향상을 위한 사용자-제품 속성 제안)

  • Hyosun An;Sunghoon Kim;Yerim Choi
    • Journal of Fashion Business
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    • v.27 no.3
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    • pp.50-62
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    • 2023
  • The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

A Method of Intonation Modeling for Corpus-Based Korean Speech Synthesizer (코퍼스 기반 한국어 합성기의 억양 구현 방안)

  • Kim, Jin-Young;Park, Sang-Eon;Eom, Ki-Wan;Choi, Seung-Ho
    • Speech Sciences
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    • v.7 no.2
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    • pp.193-208
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    • 2000
  • This paper describes a multi-step method of intonation modeling for corpus-based Korean speech synthesizer. We selected 1833 sentences considering various syntactic structures and built a corresponding speech corpus uttered by a female announcer. We detected the pitch using laryngograph signals and manually marked the prosodic boundaries on recorded speech, and carried out the tagging of part-of-speech and syntactic analysis on the text. The detected pitch was separated into 3 frequency bands of low, mid, high frequency components which correspond to the baseline, the word tone, and the syllable tone. We predicted them using the CART method and the Viterbi search algorithm with a word-tone-dictionary. In the collected spoken sentences, 1500 sentences were trained and 333 sentences were tested. In the layer of word tone modeling, we compared two methods. One is to predict the word tone corresponding to the mid-frequency components directly and the other is to predict it by multiplying the ratio of the word tone to the baseline by the baseline. The former method resulted in a mean error of 12.37 Hz and the latter in one of 12.41 Hz, similar to each other. In the layer of syllable tone modeling, it resulted in a mean error rate less than 8.3% comparing with the mean pitch, 193.56 Hz of the announcer, so its performance was relatively good.

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Analysis of major issues in the field of Maritime Autonomous Surface Ships using text mining: focusing on S.Korea news data (텍스트 마이닝을 활용한 자율운항선박 분야 주요 이슈 분석 : 국내 뉴스 데이터를 중심으로)

  • Hyeyeong Lee;Jin Sick Kim;Byung Soo Gu;Moon Ju Nam;Kook Jin Jang;Sung Won Han;Joo Yeoun Lee;Myoung Sug Chung
    • Journal of the Korean Society of Systems Engineering
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    • v.20 no.spc1
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    • pp.12-29
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    • 2024
  • The purpose of this study is to identify the social issues discussed in Korea regarding Maritime Autonomous Surface Ships (MASS), the most advanced ICT field in the shipbuilding industry, and to suggest policy implications. In recent years, it has become important to reflect social issues of public interest in the policymaking process. For this reason, an increasing number of studies use media data and social media to identify public opinion. In this study, we collected 2,843 domestic media articles related to MASS from 2017 to 2022, when MASS was officially discussed at the International Maritime Organization, and analyzed them using text mining techniques. Through term frequency-inverse document frequency (TF-IDF) analysis, major keywords such as 'shipbuilding,' 'shipping,' 'US,' and 'HD Hyundai' were derived. For LDA topic modeling, we selected eight topics with the highest coherence score (-2.2) and analyzed the main news for each topic. According to the combined analysis of five years, the topics '1. Technology integration of the shipbuilding industry' and '3. Shipping industry in the post-COVID-19 era' received the most media attention, each accounting for 16%. Conversely, the topic '5. MASS pilotage areas' received the least media attention, accounting for 8 percent. Based on the results of the study, the implications for policy, society, and international security are as follows. First, from a policy perspective, the government should consider the current situation of each industry sector and introduce MASS in stages and carefully, as they will affect the shipbuilding, port, and shipping industries, and a radical introduction may cause various adverse effects. Second, from a social perspective, while the positive aspects of MASS are often reported, there are also negative issues such as cybersecurity issues and the loss of seafarer jobs, which require institutional development and strategic commercialization timing. Third, from a security perspective, MASS are expected to change the paradigm of future maritime warfare, and South Korea is promoting the construction of a maritime unmanned system-based power, but it emphasizes the need for a clear plan and military leadership to secure and develop the technology. This study has academic and policy implications by shedding light on the multidimensional political and social issues of MASS through news data analysis, and suggesting implications from national, regional, strategic, and security perspectives beyond legal and institutional discussions.

Structural Analysis of Cooking Recipe Texts - Based on Kimchi Jjigae Recipe - (요리레시피의 텍스트 구조해석 - 김치찌개 레시피 중심으로 -)

  • Choi, Jiyu;Han, Gyusang
    • The Korean Journal of Community Living Science
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    • v.28 no.2
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    • pp.191-201
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    • 2017
  • This study compared and analyzed the structures of cooking recipes in order to identify the overall cooking method and develop an efficient method for analyzing cooking recipes. We present procedural texts using a flow graph, which can be referred to as a recipe tree, to represent cooking recipes and the database. A total of 110 kimchi jjigae recipes were identified and classified as 'portion', 'kinds of ingredients', and 'number of cooking deployment'. Recipes for two persons were the most common (43.6%), and 7-13 kinds of ingredients accounted for 50% of kimchi jjigae recipes. Kimchi presented the highest frequency at 78 cases, and pork showed the high frequency at 30 cases. To identify cooking deployment, step 6 was the highest, followed by step 5 (17.3%), step 7 (17.3%), step 4 (11.8%), and step 3 (9.1%). When analyzing the frequency of the relationship between ingredients and action in a recipe expression, Food (F) and Action by the chef (Ac) showed the highest rates at 11.29 and 12.30, respectively, in the cooking process. For frequencies of dependency relation expression in recipes, d-obj (direct object) was the highest at 13.56. The proposed method provides users more efficient and easier access to recipes suitable for their cooking skills.

Big Data Analysis of News on Purchasing Second-hand Clothing and Second-hand Luxury Goods: Identification of Social Perception and Current Situation Using Text Mining (중고의류와 중고명품 구매 관련 언론 보도 빅데이터 분석: 텍스트마이닝을 활용한 사회적 인식과 현황 파악)

  • Hwa-Sook Yoo
    • Human Ecology Research
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    • v.61 no.4
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    • pp.687-707
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    • 2023
  • This study was conducted to obtain useful information on the development of the future second-hand fashion market by obtaining information on the current situation through unstructured text data distributed as news articles related to 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods'. Text-based unstructured data was collected on a daily basis from Naver news from January 1st to December 31st, 2022, using 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods' as collection keywords. This was analyzed using text mining, and the results are as follows. First, looking at the frequency, the collection data related to the purchase of second-hand luxury goods almost quadrupled compared to the data related to the purchase of second-hand clothing, indicating that the purchase of second-hand luxury goods is receiving more social attention. Second, there were common words between the data obtained by the two collection keywords, but they had different words. Regarding second-hand clothing, words related to donations, sharing, and compensation sales were mainly mentioned, indicating that the purchase of second-hand clothing tends to be recognized as an eco-friendly transaction. In second-hand luxury goods, resale and genuine controversy related to the transaction of second-hand luxury goods, second-hand trading platforms, and luxury brands were frequently mentioned. Third, as a result of clustering, data related to the purchase of second-hand clothing were divided into five groups, and data related to the purchase of second-hand luxury goods were divided into six groups.

Design of Document Suggestion System based on TF-IDF Algorithm for Efficient Organization of Documentation (효율적인 문서 구성을 위한 TF-IDF 알고리즘 기반 문서 제안 시스템의 설계)

  • Kim, Young-Hoon;Park, Seung-Min;Cho, Dae-Soo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.527-528
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    • 2022
  • 빠르게 변하는 환경에 맞춰 평생 교육이 일반화되고 개인에게 요구되는 학습량은 많아지고 있으며 높아진 학습량에 맞게 학습 시간 단축과 효율적인 학습을 위한 학습 방법을 선택하는 것이 중요해지고 있다. 본 논문에서는 학습 정리를 위해 작성한 문서를 분석하여 해당 문서와 관련된 문서를 제안하고 본 문서와 엮어 학습을 위한 문서 묶음을 만들 수 있는 시스템을 제안한다. 문서의 유사도, 중요도를 구할 수 있는 TF-IDF를 이용하여 문서를 분석해 키워드를 추출한 다음 그와 관련된 문서를 제안하고 문서 묶음을 만들어 조회할 수 있도록 한다. 이 시스템은 학습 정리 시 관련 문서를 함께 볼 수 있도록 하고, 필요하다면 묶음으로 만들어 효과적인 학습을 위한 도구로 이용할 수 있다.

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Impact and post-impact of ring supports: Eigenfrequency response at nano-scale

  • Madiha Ghamkhar;MohamedA. Khadimallah;Muzamal Hussain;Abdelouahed Tounsi
    • Structural Engineering and Mechanics
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    • v.88 no.2
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    • pp.109-115
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    • 2023
  • In this paper, frequencies of zigzag structure of carbon nanotubes isinvestigated based on Donnell shell theory. These tubes are wrapped with the ring supports in the axial direction. The fundamental frequency curves displayed in article show the dependence of vibrations attributes to zigzag single walled carbon nanotubes. Various zigzag indices are introduced against the variation of length to predict the vibration. Also, the influence of ring supports is sketched with proposed structure for frequency analysis. The frequencies of zigzag tube decreases as the length increases. It is observed that the frequencies decreases with ring support and have higher frequencies without ring. The problem is formulated using Partial Differential Equation. Three expressions of modal deformation displacement functions is used for the elimination of temporal variation to form the solution in the eigen from. For the stability of present study the results are compared with experimentally and numerically in the open text.

Analysis of online parenting community posts on expanded newborn screening for metabolic disorders using topic modeling: a quantitative content analysis (토픽 모델링을 활용한 광범위 선천성 대사이상 신생아 선별검사 관련 온라인 육아 커뮤니티 게시 글 분석: 계량적 내용분석 연구)

  • Myeong Seon Lee;Hyun-Sook Chung;Jin Sun Kim
    • Women's Health Nursing
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    • v.29 no.1
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    • pp.20-31
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    • 2023
  • Purpose: As more newborns have received expanded newborn screening (NBS) for metabolic disorders, the overall number of false-positive results has increased. The purpose of this study was to explore the psychological impacts experienced by mothers related to the NBS process. Methods: An online parenting community in Korea was selected, and questions regarding NBS were collected using web crawling for the period from October 2018 to August 2021. In total, 634 posts were analyzed. The collected unstructured text data were preprocessed, and keyword analysis, topic modeling, and visualization were performed. Results: Of 1,057 words extracted from posts, the top keyword based on 'term frequency-inverse document frequency' values was "hypothyroidism," followed by "discharge," "close examination," "thyroid-stimulating hormone levels," and "jaundice." The top keyword based on the simple frequency of appearance was "XXX hospital," followed by "close examination," "discharge," "breastfeeding," "hypothyroidism," and "professor." As a result of LDA topic modeling, posts related to inborn errors of metabolism (IEMs) were classified into four main themes: "confirmatory tests of IEMs," "mother and newborn with thyroid function problems," "retests of IEMs," and "feeding related to IEMs." Mothers experienced substantial frustration, stress, and anxiety when they received positive NBS results. Conclusion: The online parenting community played an important role in acquiring and sharing information, as well as psychological support related to NBS in newborn mothers. Nurses can use this study's findings to develop timely and evidence-based information for parents whose children receive positive NBS results to reduce the negative psychological impact.

Analysis of News Articles on Child Welfare Policies in South Korea: K-Means Clustering (대한민국 정권별 아동복지정책 관련 뉴스 기사 분석: K-평균 군집 분석)

  • Kim, Eun Joo;Kim, Seong Kwang;Park, Bit Na
    • Journal of East-West Nursing Research
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    • v.29 no.2
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    • pp.185-195
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    • 2023
  • Purpose: The purpose of this study is to analyze changes of child welfare policies and provide insights based on the collection and classification of newspaper articles. Methods: Articles related to child welfare policies were collected from 1990, during the Kim, Young-sam administration, to May 9, 2022, under the Moon, Jae-in administration. K-Means clustering and keyword Term Frequency-Inverse Document Frequency analysis were utilized to cluster and analyze newspaper articles with similar themes. Results: The administrations of Kim, Young-sam, Kim, Dae-jung, Roh, Moo-hyun, and Park, Geun-hye were classified into two clusters, and the Lee, Myung-bak and Moon, Jae-in administrations were classified into three clusters. Conclusion: South Korea's child welfare policies have focused on ensuring the safety and healthy development of children through diverse policies initiatives over the years. However, challenges related to child protection and child abuse persist. This requires additional resources and budget allocation. It is important to establish a comprehensive support system for children and families, including comprehensive nursing support.

Text Mining-Based Analysis of Hyundai Automobile Consumer Satisfaction and Dissatisfaction Factors in the Chinese Market: A Comparison with Other Brands (텍스트 마이닝을 이용한 현대 자동차 중국시장 소비자의 만족 및 불만족 요인 분석 연구: 다른 브랜드와의 비교)

  • Cui Ran;Inyong Nam
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.539-549
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    • 2024
  • This study employed text mining techniques like frequency analysis, word clouds, and LDA topic modeling to assess consumer satisfaction and dissatisfaction with Hyundai Motor Company in the Chinese market, compared to brands such as Toyota, Volkswagen, Buick, and Geely. Focusing on compact vehicles from these brands between 2021 and 2023, this study analyzed customer reviews. The results indicated Hyundai Avante's positive factors, including a long wheelbase. However, it also highlighted dissatisfaction aspects like Manipulate, engine performance, trunk space, chassis and suspension, safety features, quantity and brand of audio speakers, music membership service, separation band, screen reflection, CarLife, and map services. Addressing these issues could significantly enhance Hyundai's competitiveness in the Chinese market. Previous studies mainly focused on literature research and surveys, which only revealed consumer perceptions limited to the variables set by the researchers. This study, through text mining and comparing various car brands, aims to gain a deeper understanding of market trends and consumer preferences, providing useful information for marketing strategies of Hyundai and other brands in the Chinese market.