An easy approach to let ChatGPT to learn your graph schema and help you construct Cypher queries — ChatGPT has taken the world by storm. It is virtually impossible to not be bombarded with various information about it. I guess it is only a matter of time before a plethora of AI-generated content hits the internet. I have been playing around with ChatGPT and trying to produce Cypher…

What’s new and what’s been deprecated in Cypher in the latest release of Neo4j — A couple of weeks ago, Neo4j 5 was released. If you are like me and have ignored all the deprecation warnings during the later Neo4j 4 version, you might have to update your Cypher queries to work with the latest Neo4j version. Luckily, there are no significant differences in the…

Combine various NLP techniques to construct a knowledge graph representing your website — A website is a reflection of the company. For the most part, it is used to inform users about various products and services and drive sales. However, the website grows and changes over time and many minor and major changes are introduced. As a result, it is not uncommon to…

Interactively analyze and visualize the family tree using Neo4j — It’s been a while since I wrote a blog post. I’ve been busy watching the House of Dragon show. However, now that the wait for season two has begun, I suddenly have some spare time on my hands. I’ve seen some social posts that describe the connections between characters in…

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. …

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…