Utilize the Neo4j Graph Data Science library to identify node roles and use them as features for the user segmentation process — Knowing your users is vital to any business. When your users can interact with each other on a social media platform, content sharing platform, or even work-related platforms, you can construct a network between your users based on their interactions and extract graph-based features to segment your users. Of course…

Utilize graph algorithms in the Neo4j Graph Data Science library to extract graph-based features and improve the accuracy of machine learning models — A wave of graph-based approaches to data science and machine learning is rising. We live in an era where the exponential growth of graph technology is predicted [1]. The ability to analyze data points through the context of their relationships enables more profound and accurate data exploration and predictions. …

Explore the NCBI taxonomy of organisms in a graph database — The evolution of life is a beautiful and insightful field of study that traces our origins back to the beginning of life. It helps us understand where we came from and where we are potentially going. The relationships between species are often depicted in the tree of life, which is…

Learn the basic syntax of the newly released Python client for Neo4j Graph Data Science — Data scientists like me love Python. It features a wide variety of machine learning and data science libraries that can help you get started on a data science project in minutes. It is not uncommon to use a variety of libraries in a data science workflow. With the release of…

Learn how to implement your custom-tailored information extraction pipeline with spaCy and store results in Neo4j — Since I first dabbled with natural language processing, I have had a special place in my heart for information extraction (IE) pipelines. Information extraction (IE) pipelines extract structured data from unstructured data like text. The internet provides an abundance of information in the form of various articles and other content…

Importing Bitcoin transactions via Python Websocket into Neo4j and monitoring them with a NeoDash dashboard — Cryptocurrencies have become more and more integrated into our daily life. Many cryptocurrencies like Bitcoin and Ethereum are decentralized networks based on blockchain technology. They have a wide array of use-cases and have been implemented by various companies and governments. One remarkable attribute of many cryptocurrencies is that all the…

Construct a biomedical knowledge graph by utilizing NLP techniques to extract relationships from biomedical articles — The biomedical domain is a prime example of finding connections and relationships between various entities like genes, drugs, diseases, and more. It is virtually impossible for any doctor to keep in touch with all the latest published research. For example, I queried PubMed Central and found 100 thousand articles published…

Utilize UK Gazette API capabilities to construct a knowledge graph and analyze it in Neo4j — I love constructing knowledge graphs from various sources. I’ve wanted to create a government knowledge graph for some time now but was struggling to find any data that is easily accessible and doesn’t require me to spend weeks developing a data pipeline. At first, I thought I would have to…

Learn the difference between APOC and native Cypher approach to batching transactions — When dealing with massive graphs and more extensive updates in Neo4j, you will likely run out of heap memory if you don’t resort to batching transactions. While you could use your favorite scripting language to batch transactions, you can also split a single Cypher query into multiple transactions directly in…