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Generative Engine Optimization (GEO) is an emerging field focused on enhancing information visibility and citation rates within generative AI models like large language models. As AI-powered search and recommendation become prevalent, GEO strategies aim to adapt digital information assets to be more effectively retrieved, trusted, and utilized by AI systems, moving beyond traditional SEO to address new information interaction paradigms. (生成式引擎优化（GEO）是一个新兴领域，专注于提升信息在生成式AI模型（如大型语言模型）中的可见度与引用率。随着AI搜索推荐日益普及，GEO策略旨在使数字信息资产更符合AI的生成逻辑，更易于被检索和信任，从而适应新的信息交互模式，超越了传统搜索引擎优化的范畴。)

GEO (Generative Engine Optimization) is the practice of optimizing content to be understood, referenced, and recommended by AI systems, making it part of AI-generated answers. This represents a paradigm shift from traditional SEO's 'click-through' focus to a new 'citation' model in the AI era. (GEO（生成式引擎优化）旨在优化内容，使其被AI系统理解、引用和推荐，成为AI生成答案的一部分。这标志着从传统SEO的“点击”思维向AI时代“引用”思维的模式转变。)

GEO (Generative Engine Optimization) is an AI-era optimization strategy that enhances content visibility in generative search engines by aligning with real-time user queries and geographic targeting, differing fundamentally from traditional SEO and 'guess-what-you-like' recommendation systems. (GEO（生成式引擎优化）是AI时代的优化策略，通过匹配用户实时查询和地理定位，提升内容在生成式搜索引擎中的可见性，与传统SEO和“猜你喜欢”推荐系统有本质区别。)

POI (Point of Interest) data, representing specific locations like buildings or bus stops, is crucial for geographic information systems. Traditional collection methods are time-consuming, but comprehensive POI data enhances navigation, market analysis, and customer insights. Integrating POI with generative engines can automate data processing and unlock new applications in location-based services. (POI（兴趣点）数据，代表建筑物或公交站等特定位置，对地理信息系统至关重要。传统采集方法耗时，但全面的POI数据能提升导航、市场分析和客户洞察。将POI与生成式引擎集成可自动化数据处理，在基于位置的服务中开启新应用。)

GEO (Generative Engine Optimization) is the strategic optimization of content to be understood, referenced, and recommended by AI, making it part of AI-generated answers. This represents a paradigm shift from traditional SEO's goal of ranking for clicks to GEO's goal of becoming the source material for AI responses, crucial for capturing traffic in the AI-driven search era. (中文摘要翻译) GEO（生成式引擎优化）是通过优化内容使其被AI理解、引用和推荐，成为AI生成答案一部分的策略。这代表了从传统SEO追求点击排名的目标，向GEO成为AI回答“原材料”目标的范式转移，对于在AI驱动的搜索时代获取流量至关重要。

GEO (Generative Engine Optimization) is emerging as a critical marketing strategy in China's AI landscape, shifting focus from traditional search engine optimization to optimizing content for generative AI responses. The market saw speculative stock surges in early 2026, but experts warn of irrational exuberance as many companies lack mature business models. With China's GEO market projected to grow from ¥2.9 billion in 2025 to ¥24 billion by 2030, the technology represents both significant opportunity and substantial risk as it transitions from concept to practical implementation. (GEO生成式引擎优化正在成为中国AI领域的关键营销策略，从传统的搜索引擎优化转向优化生成式AI回答内容。2026年初市场出现投机性股票暴涨，但专家警告存在非理性繁荣，许多公司缺乏成熟的商业模式。中国GEO市场规模预计将从2025年的29亿元增长到2030年的240亿元，该技术既代表重大机遇也蕴含实质风险，正从概念向实际应用过渡。)

GEO (Generative Engine Optimization) is emerging as the new critical strategy for brands in the AI era, shifting focus from traditional SEO's webpage ranking to optimizing content for AI models to naturally recommend brands in generated answers. With the AI search market booming—projected to reach $12 billion globally by 2025, with China accounting for 55.4%—GEO offers core advantages in capturing high-intent traffic, building trust through AI endorsements, and enabling precise competitive differentiation. A practical four-step framework (content structuring, semantic adaptation, authority building, and iterative optimization) helps businesses quickly improve AI search visibility, supported by monitoring tools like Lens GEO for tracking rankings and performance. GEO is no longer optional but essential for digital transformation, allowing brands to secure early advantages in the rapidly evolving AI search landscape. (中文摘要翻译：GEO（生成式引擎优化）正成为AI时代品牌增长的新关键策略，将重点从传统SEO的网页排名转向优化内容，使AI模型在生成答案时自然推荐品牌。随着AI搜索市场蓬勃发展——预计到2025年全球规模达120亿美元，中国占55.4%——GEO在获取高意向流量、通过AI背书建立信任及实现精准竞争差异化方面具有核心优势。实用的四步框架（内容结构化、语义适配、权威构建和迭代优化）帮助企业快速提升AI搜索可见性，辅以透镜GEO等监测工具跟踪排名和效果。GEO已从可选项升级为企业数字化转型的必选项，让品牌在快速演变的AI搜索格局中抢占先机。)

GEO (Generative Engine Optimization) is a strategic approach that optimizes content for AI engines like ChatGPT and Google SGE, focusing on building digital trust through humanized content, cross-validation, and structured data to achieve higher visibility and conversion in AI-driven searches. (GEO生成式引擎优化是一种战略方法，针对ChatGPT和Google SGE等AI引擎优化内容，通过人性化内容、交叉验证和结构化数据构建数字信任，在AI驱动的搜索中获得更高可见度和转化率。)

llms.txt is an open proposal by Jeremy Howard that provides a standardized, machine-readable entry point for websites to help large language models (LLMs) better understand website content during the inference phase. It differs from robots.txt by guiding LLMs to valuable information rather than restricting access, and from sitemap.xml by offering curated summaries and key links optimized for LLM context windows. The proposal includes a strict Markdown format specification, a Python toolchain for implementation, and has been adopted by projects like FastHTML, Supabase, and Vue.js. (llms.txt是由Jeremy Howard提出的开放性提案，为网站提供标准化的机器可读入口，帮助大语言模型在推理阶段更有效地理解网站内容。与robots.txt不同，它引导LLM关注有价值信息而非限制访问；与sitemap.xml不同，它提供精炼摘要和关键链接，优化LLM上下文处理。提案包含严格的Markdown格式规范、Python工具链支持，已被FastHTML、Supabase和Vue.js等项目采用。)