Sensibility Ergonomics Design Recommendation System Using Weather WebBot

Analysis of a customer´s sensibility and preferences is an important strategy in a market that is becoming increasingly more customer oriented. In this paper, we propose the sensibility ergonomics design recommendation system using weather WebBot (DRS-WB). The proposed method applies sensibility ergonomics to increase the efficiency of merchandising for human-oriented sensible product designs. Development of DRS-WB used a user interface and collaborative filtering for the textile and fashion designs in order to satisfy the user´s needs. Collaborative filtering was adopted in order to recommend designs of interest for users based on the predictive relationship discovered between the current user and other previous users. The today weather information is simultaneously acquired from the sensor based smartwear and the weather WebBot (Web Robot Agent). The weather WebBot uses a database of weather forecast information extracted from the web pages and RSS of the Korea Meteorological Administration and collects information from the various links off the main URL. And its signals are transmitted to the connected DRS-WB. It can be easily monitored in real time. We used 60 textile designs and 41 fashion designs in the survey questionnaire. The composition of the questionnaire is 17 sections for 6 designs on a page. 2,830,020 ratings were collected from 1,401 users. The pictures of fashion design details, such as collar type, sleeve type, skirt type, skirt length, and color tone were evaluated in terms of sensibility. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity of this system.