grakn - The Knowledge Graph

•    Java

The Knowledge Graph

Awesome-Coder - :books: Interactive MindMap, RoadMap(Learning Path/Interview Questions), xCompass, Weekly for Developer, to Learn Everything in ITCS :dizzy: 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

:books: Interactive MindMap, RoadMap(Learning Path/Interview Questions), xCompass, Weekly for Developer, to Learn Everything in ITCS :dizzy: 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

Coder-Roadmap - :books: Interactive MindMap, RoadMap(Learning Path/Interview Questions), xCompass, Weekly for Developer, to Learn Everything in ITCS :dizzy: 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

:books: Interactive MindMap, RoadMap(Learning Path/Interview Questions), xCompass, Weekly for Developer, to Learn Everything in ITCS :dizzy: 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

AmpliGraph - Python library for Representation Learning on Knowledge Graphs https://docs

•    Python

Open source library based on TensorFlow that predicts links between concepts in a knowledge graph. AmpliGraph is a suite of neural machine learning models for relational Learning, a branch of machine learning that deals with supervised learning on knowledge graphs.

Research - novel deep learning research works with PaddlePaddle

•    Python

novel deep learning research works with PaddlePaddle

dgl-ke - High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings

•    Python

Knowledge graphs (KGs) are data structures that store information about different entities (nodes) and their relations (edges). A common approach of using KGs in various machine learning tasks is to compute knowledge graph embeddings. DGL-KE is a high performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings. The package is implemented on the top of Deep Graph Library (DGL) and developers can run DGL-KE on CPU machine, GPU machine, as well as clusters with a set of popular models, including TransE, TransR, RESCAL, DistMult, ComplEx, and RotatE. This command will download the FB15k dataset, train the transE model and save the trained embeddings into the file.

TypeDB - A strongly-typed database

•    Java

TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language. TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.

awesome-network-embedding - A curated list of network embedding techniques.

Also called network representation learning, graph embedding, knowledge embedding, etc. The task is to learn the representations of the vertices from a given network.

Logseq - Platform for knowledge management and collaboration.

•    Clojure

Logseq is a platform for knowledge management and collaboration. It focuses on privacy, longevity, and user control. The server will never store or analyze your private notes. It works on top of local plain-text Markdown and Org-mode files. Use it to write, organize and share your thoughts, keep your to-do list, and build your own digital garden. It provides support to organize your tasks and projects with built-in workflow commands.

kglib - Grakn Knowledge Graph Library (ML R&D)

•    Python

To respond to these scenarios, KGLIB is the centre of all research projects conducted at Grakn Labs. In particular, its focus is on the integration of machine learning with the Grakn Knowledge Graph. More on this below, in Knowledge Graph Tasks. At present this repo contains one project: Knowledge Graph Convolutional Networks (KGCNs). Go there for more info on getting started with a working example.

RUBRIX - Python framework to explore, label, and monitor data for NLP

•    Python

Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects. Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Rubrix is designed to close this gap, enabling you to iterate as much as you need.

Geist - A personal knowledge base with a focus on connections

•    Javascript

A personal knowledge base with a focus on connections. The personal knowledge base (PKB) is basically a wiki system for personal use. Unlike a public wiki which most often focuses on representing facts, the PKB can contain subjective material relevant to the person or persons using the PKB. Therefore the desired properties of a PKB are equivalent to those of the personal wiki.

atomspace - The OpenCog hypergraph database, query system and rule engine

•    C++

The OpenCog AtomSpace is a knowledge representation (KR) database and the associated query/reasoning engine to fetch and manipulate that data, and perform reasoning on it. Data is represented in the form of graphs, and more generally, as hypergraphs; thus the AtomSpace is a kind of graph database, the query engine is a general graph re-writing system, and the rule-engine is a generalized rule-driven inferencing system. The vertices and edges of a graph, known as "Atoms", are used to represent not only "data", but also "procedures"; thus, many graphs are executable programs as well as data structures. The AtomSpace is a platform for building Artificial General Intelligence (AGI) systems. It provides the central knowledge representation component for OpenCog. As such, it is a fairly mature component, on which a lot of other systems are built, and which depend on it for stable, correct operation in a day-to-day production environment.

retailscm-biz-suite - 供应链，零售供应链中台系统，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，通过REST接口调用，前后端完全分离。

•    Java

供应链，零售供应链中台系统，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，通过REST接口调用，前后端完全分离。

graph-pattern-learner - Evolutionary Graph Pattern Learner that learns SPARQL queries for a given set of source-target-pairs from an endpoint

•    Python

In this repository you find the code for a graph pattern learner. Given a list of source-target-pairs and a SPARQL endpoint, it will try to learn SPARQL patterns. Given a source, the learned patterns will try to lead you to the right target. As you can immediately see, associations don't only follow a single pattern. Our algorithm is designed to be able to deal with this. It will try to learn several patterns, which in combination model your input list of source-target-pairs. If your list of source-target-pairs is less complicated, the algorithm will happily terminate earlier.

deepamehta - Platform for collaboration and knowledge management

•    Java

DeepaMehta 4 is a platform for collaboration and knowledge management. The vision of DeepaMehta is a Post-Desktop Metaphor user interface that abolishes applications, windows, files, and folders in favor of stable personal views of contextual content. The goal of DeepaMehta is to provide knowledge workers of all kind a cognitive adequate work environment, right after your desktop computer or laptop has booted up. Technically DeepaMehta 4 is made of Server-side: Java, Neo4j, Lucene, Apache Felix (OSGi), Jetty, Jersey, Thymeleaf (optional), Neo4j Spatial (optional), Jetty WebSocket (optional), Karaf (optional), Pax Web (optional). Client-side: Javascript, jQuery, jQuery-UI, HTML5 Canvas, CKEditor, OpenLayers (optional), D3.js (optional).

KBox - 📦 The Knowledge Box

•    Java

KBox is an abbreviation for Knowledge Box. The rationale behind KBox is to allow users to have a single place to share resources and knowledge among different applications as well as instances. Moreover, working on top of RDF model, KBox is a natural extension of the Web on your computer. Systems usually deal with resources and knowledge that are often duplicated among several instances. For instance, when using the Stanford NLP library the resources and knowledge inside the library are duplicated among different applications. The idea is to have a common repository where users can share resources without duplication. In order to do that, we bring the RDF concept to bridge the gap among reource publishig, storing and locating.

nexus - Blue Brain Nexus - A knowledge graph for data-driven science

•    Jupyter

The Blue Brain Nexus is a provenance based, semantic enabled data management platform enabling the definition of an arbitrary domain of application for which there is a need to create and manage entities as well as their relations (e.g. provenance). For example, the domain of application managed by the Nexus platform deployed at Blue Brain is to digitally reconstruct and simulate the brain. Register and manage neuroscience relevant entity types through schemas that can reuse or extend community defined schemas (e.g. schema.org, bioschema.org, W3C-PROV) and ontologies (e.g. brain parcellation schemes, cell types, taxonomy).

Piggydb - Piggydb is a Web notebook application that provides you with a platform to build your knowledge personally or collaboratively

•    Java

Piggydb is a Web notebook application that provides you with a platform to build your knowledge personally or collaboratively.

DataReused - Get Data Reused

Data reuse is the process of leveraging an existing dataset to fulfill a valuable mission with positive reward. The valuation of dataset closely depends on how well it gets reused. A dataset, regardless how hard it was produced and how easy it could be reused, will perish if it is not used by anyone. Data reuse with positive reward increases social welfare and keeps data reuse ecosystem healthy. There are a lot of ways to get data reused, e.g. data visualization, data sharing, data conversion, data linking, data fusion, and data cleaning. The issue tracker https://github.com/lidingpku/DataReused/issues is repurposed to host my thoughts and dicussions on relevant topics.