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GraphRAG is a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting a knowledge graph out of raw text, building a community hierarchy, generating summaries for these communities, and then leveraging these structures when performing RAG-based tasks. It aims to improve LLM outputs using real-world information, particularly for reasoning about private datasets that the LLM has not been trained on. GraphRAG shows substantial improvements in answering complex questions by utilizing knowledge graphs and community summaries.
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技术使用统计数据和市场份额
您可以通过筛选地理位置、行业、公司规模、收入、技术使用情况、职位等来根据您的需求定制这些数据。您可以以Excel或CSV格式下载数据。
您可以获得有关此数据的提醒。您可以通过选择您感兴趣的技术来开始,然后当有新公司使用该技术时,您将会在您的收件箱中收到提醒。
公司
您可以将这些数据导出到一个Excel文件,然后导入到您的CRM中。您也可以将这些数据导出到API。
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