HUI-PING TSERNGChang, Chung-ChoChung-ChoChangTai, Shu-HsienShu-HsienTaiLiu, Hexu2025-08-142025-08-142025-07-0716878086https://www.scopus.com/record/display.uri?eid=2-s2.0-105009925402&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/731421Material selection is a challenging and essential research area in architectural design, as it plays a key role across project phases. Architects must consider both quantifiable material properties (such as durability, cost, and environmental impact) and qualitative aspects (such as texture and color) that influence a building’s appearance, longevity, and environmental fit. Relying solely on traditional data often limits architects’ understanding, especially during early design, where material choices impact overall performance. This complexity highlights the need for an efficient recommendation system. This study proposes an innovative recommendation system that uses feature engineering to optimize material selection. By integrating materials into early design with enhanced feature engineering and a comprehensive database, this system supports diverse professional needs. A practical case demonstrates its ability to improve material selection efficiency and accuracy, making it an making it an indispensable tool for specialized users in informed decision-making.falsearchitectural designcloud databasefeature engineeringselected materialssortable hashtag[SDGs]SDG6[SDGs]SDG7[SDGs]SDG9[SDGs]SDG11[SDGs]SDG12[SDGs]SDG13[SDGs]SDG14[SDGs]SDG15journal article10.1155/adce/78866132-s2.0-105009925402