Articles by Gina Assaf
Gina Assaf is an interaction designer at Prismatic, an internet and media tech startup company in San Francisco, focused on using machine learning to recommend relevant content to users based on their interests. Gina has a Masters in Human Computer Interaction from Carnegie Mellon University and a Bachelors in Computer Science. She is passionate about understanding users and designing thoughtful products that solve important and real user needs. Twitter: @GinaAssaf
[:en]Helping Software Learn: Designing for Recommendation Engines[:zh]帮助软件学习：推荐引擎的设计[:KO]소프트웨어 배우기 안내: 추천 엔진 설계하기[:pt]Ajudar o software a aprender: Projetar para mecanismos de recomendação[:ja]ソフトウェアの学習支援：レコメンデーションエンジンのデザイン[:es]Cómo ayudar a que el software “aprenda”: Diseñar para los motores de recomendación[:]
[:en]Products based on personalized recommendations can make content more relevant and compelling, as long as they are designed to minimize effort for users and maximize transparency.[:zh]对于基于个性化推荐的产品而言，只要最大限度地减少用户付出并提高透明度，即可提高内容的相关性和吸引力。[:KO]개인 맞춤형 추천 기반의 제품들이 사용자의 노력을 최소화하고 투명성을 극대화할 수 있도록 설계된다면 콘텐츠가 더욱 적절하고 흥미진진해질 것입니다.[:pt]Os produtos baseados em recomendações personalizadas podem tornar o conteúdo mais relevante e convincente, desde que sejam projetadas para minimizar o trabalho e maximizar a transparência.[:ja]個別化されたレコメンデーション（推奨）に基づく製品は、ユーザーにかかる負担を最小限にとどめ、透明性を最大化するデザインである限り、コンテンツにさらなる関連性と説得力を持たせることができる。[:es]Los productos basados en las recomendaciones personalizadas pueden hacer que el contenido sea más relevante y persuasivo, siempre que estén diseñados con el objeto de minimizar el esfuerzo para los usuarios y maximizar la transparencia.[:]
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