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Who can introduce me to x?
Who is the most connected person?
Predict potential connections
- Scalable
Designed from ground up to scale enterprise use cases - Simple Ingestion
Easy integration in existing data infrastructure + connectors to all leading data processing and data ecosystems - Open Source
Extensibility, Community, especially large community maintained library - NLP Support
Built-In Text Processing, Search, and Similarity Ranking
Tutorials
ArangoDB and NetworkX
Property Graph Queries
In this notebook, we explore some basic graph queries using ArangoDB, including simple traversals and shortest path queries.
Professional
NLP with ArangoSearch
ArangoSearch provides information retrieval features, natively integrated into ArangoDB’s query language and with support for all data models. It is primarily a full-text search engine, a much more powerful alternative to the full-text index type.
Graph Analytics
Collaborative Filtering
We have all seen product recommendations like “People who have looked that item x, also bought item y.” For this, we consider a simple dataset with user ratings for movies and then use a technique called Collaborative Filtering to identify which new movies might be worth watching based on other movies we liked.
Graph Analytics
Fraud Detection
As you for sure know, money laundering and fraud is kind of a thing and a bad one. Over the years, fraudsters and money launderers got more sophisticated in hiding their money transfers.
Graph Analytics
Retail Data
This series of notebooks will explore the utility of ideas from graph analytics to analyze data from an online retail store. Analyze customer shopping data to determine loyal customer shopping preferences and improve their shopping experience.
R Driver
This notebook will provide an overview of the steps involved in using R and ArangoDB to work with Graph data. To do so, we will need the ArangoDB R driver.
Graph Embeddings
This notebook provides a first look at generating graph embeddings with our IMDB dataset. Generate movie recommendations with graph embeddings and store them in ArangoDB.
ArangoGraph Insights Platform now comes with built-in example guides such as an extension to our Graph Embeddings notebook; create a new deployment and go to the examples tab to get started!
Use Cases
Fraud Detection & Analytics
Today’s criminals are constantly coming up with new techniques to hide their activities by forming fraud networks with stolen or synthetic identities.
Enterprise Knowledge Graphs
Enterprise Knowledge Graphs (EKGs) have been on the rise and are incredibly valuable tools for harmonizing internal and external data relevant to an organization into a common semantic model. Enterprises benefit from improved operational efficiency and competitive advantages for their business units.
