Top 10 Knowledge Graph Datasets for Machine Learning

Are you looking for the best knowledge graph datasets for machine learning? Look no further! In this article, we will explore the top 10 knowledge graph datasets that are perfect for machine learning applications.

But first, let's define what a knowledge graph is. A knowledge graph is a type of database that stores information in a graph format. It is designed to represent knowledge in a way that is easily understandable by both humans and machines. Knowledge graphs are used in a variety of applications, including search engines, recommendation systems, and chatbots.

Now, let's dive into the top 10 knowledge graph datasets for machine learning.

1. Freebase

Freebase is a large, collaborative knowledge graph that was acquired by Google in 2010. It contains over 2.5 billion facts about people, places, and things. Freebase is a great dataset for machine learning because it is well-structured and contains a lot of information.

2. DBpedia

DBpedia is a community-driven knowledge graph that extracts structured information from Wikipedia. It contains over 5.8 million entities and 1.4 billion facts. DBpedia is a great dataset for machine learning because it is constantly updated and contains a lot of information about a wide range of topics.

3. YAGO

YAGO is a knowledge graph that contains information about entities, such as people, organizations, and locations. It contains over 10 million entities and 120 million facts. YAGO is a great dataset for machine learning because it is well-structured and contains a lot of information about a wide range of entities.

4. Wikidata

Wikidata is a free, collaborative knowledge graph that contains information about entities, such as people, places, and things. It contains over 90 million entities and 1.2 billion facts. Wikidata is a great dataset for machine learning because it is constantly updated and contains a lot of information about a wide range of entities.

5. WordNet

WordNet is a lexical database that contains information about words and their meanings. It contains over 155,000 words and 117,000 synsets. WordNet is a great dataset for machine learning because it contains a lot of information about the meanings of words, which can be used in natural language processing applications.

6. ConceptNet

ConceptNet is a knowledge graph that contains information about concepts and their relationships. It contains over 5 million assertions and covers a wide range of topics. ConceptNet is a great dataset for machine learning because it contains a lot of information about the relationships between concepts, which can be used in natural language processing applications.

7. NELL

NELL is a knowledge graph that was created by researchers at Carnegie Mellon University. It contains over 2 million entities and 15 million facts. NELL is a great dataset for machine learning because it is constantly updated and contains a lot of information about a wide range of entities.

8. OpenCyc

OpenCyc is a knowledge graph that contains information about concepts and their relationships. It contains over 239,000 concepts and 2.7 million assertions. OpenCyc is a great dataset for machine learning because it contains a lot of information about the relationships between concepts, which can be used in natural language processing applications.

9. Probase

Probase is a knowledge graph that was created by researchers at Microsoft Research. It contains over 1.5 million concepts and 15 million assertions. Probase is a great dataset for machine learning because it is well-structured and contains a lot of information about a wide range of concepts.

10. Google Knowledge Graph

Google Knowledge Graph is a knowledge graph that is used by Google to enhance its search results. It contains information about entities, such as people, places, and things. Google Knowledge Graph is a great dataset for machine learning because it is constantly updated and contains a lot of information about a wide range of entities.

In conclusion, these are the top 10 knowledge graph datasets for machine learning. Each dataset has its own strengths and weaknesses, but all of them are great resources for machine learning applications. Whether you are working on a search engine, recommendation system, or chatbot, these datasets can help you build a better product. So, what are you waiting for? Start exploring these datasets today!

Editor Recommended Sites