由設計師 Hive AI 創作嘅 Hive AI 知識圖譜平台係備受推崇嘅 2025 A' Design Award 銀獎得獎作品，獲獎類別為介面、互動及用戶體驗設計。

銀介面· 2025

Hive AI 知識圖譜平台

由 Hive AI

客戶: Hive AI

介面類別嘅 A' Design Award 銀獎得獎者

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經驗證嘅獲獎者

驗證設計 #169652 嘅獲獎狀態

喺 A' Design Award 查看新聞稿獎項徽章

色彩

設計

關於 Hive AI 知識圖譜平台

Hive AI 係一個為學習者、專業人士同研究人員而設嘅知識圖譜平台。平台採用六邊形知識節點,將零散嘅資訊構建成互相連結嘅知識體系。用戶可以上載文字、影片同圖像,人工智能會建議關聯連結、將相關內容分組,並識別知識缺口。非線性導航支援自由探索,取代固定嘅問答路徑。視覺化模板,例如歷史時間線同三維六邊形圖譜,將知識清晰呈現。響應式介面支援淺色同深色主題。

榮譽認可

關於A' Design Award 銀獎

Hive AI 知識圖譜平台是 A' Design Award 銀獎得主，這是授予頂級、華美而令人印象深刻的設計的極為崇高的認可。銀獎得主是極其卓越、極具創造力的作品，展現出其設計師傑出的專業技能、才華與敏銳。預計Hive AI 知識圖譜平台將成為一件出色的典範之作，兼具非凡的專業性與深刻的創新性。這件贏得 A' Design Award 銀獎的設計是一項備受矚目、令人欽佩的發明，造福並拓展藝術、科學、設計和技術的界限。Hive AI 知識圖譜平台是一件令人羨慕的創作，它喚起渴望，帶來積極的情感，並激發驚嘆與讚嘆。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: Hive AI is a transformative learning platform that enables learners to build personalized knowledge systems. With the unique “hexagon knowledge nodes” and AI-driven tools like tailored recommendations, knowledge grouping, and dynamic data visualization, Hive supports students, professionals, and researchers in fostering interdisciplinary exploration and managing complex information.
尺寸同包裝: Designed for adaptability, efficiency, and reliability, the platform features a responsive interface optimized for various screen sizes, supporting landscape and portrait modes. Users can personalize their experience with light and dark themes, while cross-device compatibility ensures accessibility. AI-driven adaptability enhances learning preferences, providing real-time interactions with secure performance. Hive AI integrates technical precision with user-friendly design, delivering a dynamic, intuitive experience tailored to individual needs.
標籤: Geneartive AI, Adaptive Learning, Personalization, Ed-Tech, Non-linear Interaction, Data Visualization
生產技術: Hive AI's technology was developed through an iterative, data-driven approach leveraging advanced neural networks. The product mission guided development, ensuring the machine learning framework effectively organizes users' thoughts into structured knowledge. Rigorous testing and refinement perfected the node-based architecture for seamless non-linear exploration. The final system prioritizes adaptability, efficiency, and reliability, empowering users with a dynamic, personalized learning experience.
設計挑戰: How can node-based interactions feel as intuitive as conversation-based AI? This challenge explores motion design, iconography, and cognitive flow for seamless user adaptation. By researching existing node-based systems, the effectiveness in guiding eye movement and mental mapping was evaluated, identifying both strengths and gaps. Through user testing, motion and icons for clarity and usability were refined. The goal is to create a visually intuitive, AI-assisted system that preserves familiar interaction patterns while enhancing how users navigate complex knowledge structures with ease and engagement.
研究: Type:
Competitive & User-Centered Design Research

Objective:
Enhance exploratory, autonomous learning with AI-powered tools.

Methodology:
Surveys, interviews, and usability testing.

Tools:
Google Forms, SurveyMonkey, Zoom, Figma prototypes.

Participants:
100 technology enthusiasts

Results:
Optimized node connection interactions.
Improved accessibility with refined UI.
Prioritized key data visualization methods.

Insights & Impact:
AI-driven design enhances learning efficiency, accessibility, and critical thinking, fostering a more engaging and effective digital education experience.
靈感: Hive AI epitomizes usability, efficiency, speed, and reliability. Drawing on generative AI and mind-mapping, it transforms learning into a dynamic, personalized journey. Market research shows 78% of users find current tools limiting, revealing a major business opportunity. With elegant simplicity, fluid design, and smart organization, Hive AI redefines learning and unleashes creativity.
項目時長: Research - 1 Month

Concept and Prototyping - 2 Months
Design Finalization - 1.5 Months

Evolutives & APP Development: ongoing
操作流程: The system structures fragmented information into interconnected knowledge. Learners upload and organize content - text, videos, and images - and AI enhances connections and identifies gaps.

- Node Expansion builds knowledge structures based on interests.
- Gap Bridging links concepts for deeper understanding.
Structured Organization groups information for easier memorization.
- Nonlinear Exploration enables dynamic navigation.

Hive AI also provides visual templates, like historical timelines and 3D hexagonal maps, making knowledge presentation more intuitive and effective.
專利: Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen
團隊成員: Yongwen Dai
Xuefei Wang
Keqing (Clara) Jiao
Hanyong Yang
Huiyang Chen
圖片來源: Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen