Over 10,000 physical typewritten documents from 1932 to 1941 had to be digitised, structured, and connected in order to create a single, centralised source of knowledge, for enabling the analysis of historical processes.
Crafted by our experience, this e-book propose a three-step process to leverage knowledge graph for criminal intelligence. Understand how intelligence agencies organise, compile and query vast amounts of varied data rapidly, opening up a realm of limitless possibilities for further analysis and applications such as intelligence automation or pattern recognition.
Entity Resolution (ER) draws connections between scattered, incomplete, and inconsistent records to resolve unique entities. ER is relevant in intelligence analysis, in which organized, complete, and consistent information is crucial for empowering investigations in different areas. This session shows with practical examples the role of the graph as a powerful tool for improving traditional ER. We expose its multiple capabilities: the flexibility of data representation, the application of predictive analysis and machine learning algorithms, and the opportunity to explore the data using network-based visualizations. We show end-to-end pipelines, from data ingestion to downstream analysis, discussing good practices and challenges.
Entity Resolution (ER) draws connections between scattered, incomplete, and inconsistent records to resolve unique entities. ER is relevant in intelligence analysis, in which organized, complete, and consistent information is crucial for empowering investigations in different areas. This session shows with practical examples the role of the graph as a powerful tool for improving traditional ER. We expose its multiple capabilities: the flexibility of data representation, the application of predictive analysis and machine learning algorithms, and the opportunity to explore the data using network-based visualizations. We show end-to-end pipelines, from data ingestion to downstream analysis, discussing good practices and challenges.
In this video, we will present how Knowledge Graphs and Hume streamline Tax Office investigations. In particular, we are assuming the position of an investigator examining Businesses with potential Fraudulent claims for VAT Returns. The right tool enables investigators to understand and interpret relevant data much deeper and quicker, including proactively detecting complex patterns. This way, we help Tax Departments save millions of Euros from false refunds.
Over 10,000 physical typewritten documents from 1932 to 1941 had to be digitised, structured, and connected in order to create a single, centralised source of knowledge, for enabling the analysis of historical processes.
Hume provides a single view of intelligence enabling analysts to quickly identify links and patterns of interest in the vast amounts of information they have access to. On a single canvas, analysts quickly find connections between entities, understand geographical and temporal context, and perform advanced network analysis.
Learn more about how Law enforcement agencies are already using Hume to power their intelligence analysis and achieve success.
Easily converting multiple distributed data sources into a single, connected source of truth, is the start of a great graph-native intelligence analysis.
Hume Orchestra is used for data ingestion from a wide range of systems and formats into Neo4j graph database, but it is not limited to ingestion only. Amongst others, Orchestra is capable of applying Machine Learning to your data, enriching it from external sources through API calls or performing advanced Graph Data Science algorithms. And in the end, it combines and connects all data in 1 source of truth, the Knowledge Graph.
Read more about the benefits of Enterprise Data Orchestration and unlock the full potential of your data.
*The data used in the video are entirely fictitious.
In association with The Times, Raconteur published the Fraud & Financial Crime 2023 report.
"Economic downturns have a habit of becoming a breeding ground for fraud. And with social media, cryptocurrencies and non-financial sectors such as property, fine art and jewellery also proving hotspots for financial crime, there are plenty of dangers to watch out for. Will regulators be able to keep up in this constantly evolving landscape?"
In the realm of intelligence analysis, data often needs to be contextualised within geographic or temporal frameworks. Through Geospatial Analysis, Hume provides visibility into the locations of the data, while Temporal Analysis allows for a deeper understanding of the data's evolution over time.
This video will demonstrate how Hume's Temporal and Geospatial Analysis features revolutionise police investigations. By leveraging Hume's powerful graph analytics engine, investigators are able to quickly analyse temporal and geospatial data, providing valuable insights into suspects and their co-defendants. This allows police to uncover the timeline and locations of criminal activity, such as the positioning of a cell phone or a vehicle and its changes over time, which can lead to the identification of a primary suspect and their possible accomplices.
The Temporal and Geospatial Analysis capabilities of Hume provide invaluable context, allowing for more intuitive analysis than would otherwise be possible.
*The data used in the video are entirely fictitious.
Hume is lauded for its ability to customise the system's features and tasks, giving analysts the power to tailor it to their individual needs. Its impressive internal creative capabilities, in combination with features such as Styling, Grouping and Computed Attributes, allow users to maintain full control over the system.
In this video, we will demonstrate how Hume enables effective navigation of a knowledge graph with its Styling features. During a data analysis session, it is paramount to be able to differentiate between various entities and relationships. Hume allows users to customise, style, and display the nodes and relationships on the canvas according to the requirements of the investigation.
The features of Hume offer almost limitless flexibility and styling options for graph visualisations, allowing end-users to quickly traverse their graphs. Check our website to learn more about the features that will bolster intelligence analysis.
*The data used in the video are entirely fictitious.
