A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: http://trello.com/b/8txSM12G/roadmap
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Updated
Dec 30, 2024 - Clojure
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: http://trello.com/b/8txSM12G/roadmap
Build your personal knowledge base with Trilium Notes
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
Athens is no longer maintainted. Athens was an open-source, collaborative knowledge graph, backed by YC W21
Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️♂️
搜索所有中文NLP数据集,附常用英文NLP数据集
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Mobile first Note Taking integrated with Git
A unified, comprehensive and efficient recommendation library
📚 To Be Professional Developer From Zero To Mastery, Interactive MindMap, RoadMap(Learning Path/Interview Questions), xCompass, Weekly for Developer, to Learn Everything in ITCS 💫 程序员的技术视野、知识管理与职业规划,提高个人与团队的研发效能
Neo4j graph construction from unstructured data using LLMs
A curated list of network embedding techniques.
供应链中台系统基础版,集成零售管理, 电子商务, 供应链管理, 财务管理, 车队管理, 仓库管理, 人员管理, 产品管理, 订单管理, 会员管理, 连锁店管理, 加盟管理, 前端React/Ant Design, 后端Java Spring+自有开源框架,全面支持MySQL, PostgreSQL, 全面支持国产数据库南大通用GBase 8s,通过REST接口调用,前后端完全分离。
中文医学NLP公开资源整理:术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
Awesome papers about unifying LLMs and KGs
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
利用网络上公开的数据构建一个小型的证券知识图谱/知识库
KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.
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