{"title":"采用多模态和生成式人工智能的设计研究方法:用数据驱动的分析方法强化人种学方法论","authors":"Penalva Tebar Jose Miguel, Ken Nah","doi":"10.46248/kidrs.2023.4.27","DOIUrl":null,"url":null,"abstract":"This research examines the application of Multimodal and Generative AI in analyzing interior design trends within the South Korean market. The objective is to enhance traditional ethnographic research methods with AI's quantitative capabilities, offering a more comprehensive understanding of design preferences. This methodology uses AI tools to systematically analyze and categorize design elements from a large dataset of interior design images sourced from a relevant online platform. This process involves extracting key visual trends and patterns using AI-driven semantic analysis and clustering techniques. The study identifies and classifies four dominant design trends, providing a structured overview of current market preferences. By integrating AI into design trend analysis, the study demonstrates a novel approach to understanding consumer preferences, potentially influencing future design decisions. This use of AI in design research broadens the scope of traditional ethnographic studies in design and provides practical insights for designers and industry practitioners, suggesting a shift towards more data-driven design practice.","PeriodicalId":267590,"journal":{"name":"Korea Institute of Design Research Society","volume":"60 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"멀티모달 및 생성 AI를 통한 디자인 연구방법: 민족지학적 방법론을 데이터 기반 분석으로 강화하기\",\"authors\":\"Penalva Tebar Jose Miguel, Ken Nah\",\"doi\":\"10.46248/kidrs.2023.4.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research examines the application of Multimodal and Generative AI in analyzing interior design trends within the South Korean market. The objective is to enhance traditional ethnographic research methods with AI's quantitative capabilities, offering a more comprehensive understanding of design preferences. This methodology uses AI tools to systematically analyze and categorize design elements from a large dataset of interior design images sourced from a relevant online platform. This process involves extracting key visual trends and patterns using AI-driven semantic analysis and clustering techniques. The study identifies and classifies four dominant design trends, providing a structured overview of current market preferences. By integrating AI into design trend analysis, the study demonstrates a novel approach to understanding consumer preferences, potentially influencing future design decisions. This use of AI in design research broadens the scope of traditional ethnographic studies in design and provides practical insights for designers and industry practitioners, suggesting a shift towards more data-driven design practice.\",\"PeriodicalId\":267590,\"journal\":{\"name\":\"Korea Institute of Design Research Society\",\"volume\":\"60 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korea Institute of Design Research Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46248/kidrs.2023.4.27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korea Institute of Design Research Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46248/kidrs.2023.4.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
멀티모달 및 생성 AI를 통한 디자인 연구방법: 민족지학적 방법론을 데이터 기반 분석으로 강화하기
This research examines the application of Multimodal and Generative AI in analyzing interior design trends within the South Korean market. The objective is to enhance traditional ethnographic research methods with AI's quantitative capabilities, offering a more comprehensive understanding of design preferences. This methodology uses AI tools to systematically analyze and categorize design elements from a large dataset of interior design images sourced from a relevant online platform. This process involves extracting key visual trends and patterns using AI-driven semantic analysis and clustering techniques. The study identifies and classifies four dominant design trends, providing a structured overview of current market preferences. By integrating AI into design trend analysis, the study demonstrates a novel approach to understanding consumer preferences, potentially influencing future design decisions. This use of AI in design research broadens the scope of traditional ethnographic studies in design and provides practical insights for designers and industry practitioners, suggesting a shift towards more data-driven design practice.