![]() ![]() For example, during a complex investigation you may want to eliminate (ie hide) all addresses where the “Country” property of a node equals “England”. Advanced filtering capabilities, such as the ability to remove or hide nodes or edges based on a specific property. Link prediction algorithms help uncover and find unobserved relationships, ie they predict how likely it is for there to be an edge between a given pair of nodes.In addition to graph algorithms that describe the topology of a network, we are including a number of other AI capabilities, such as to the ability to use NLP techniques to extract information (eg values, dates, entities) from unstructured documents such as invoices, emails, legal contracts, letters, reports and so.ģ.Similarity algorithms which can detect how “close” two nodes in the graph are based on the neighbourhoods around them.It is also critical when following-the-money, ie knowing the ultimate beneficiaries and who was involved in the chain of transactions. In fraud work, such applications include filtering transactions that have extremely short paths between people. Pathfinding and search algorithms which can calculate the shortest, fastest, or most optimal path between nodes.In fraud and criminal analytics, it is critical to identify ring-leaders of organised crime as they exert significant influence over their network. Centrality algorithms help to identify important nodes.In fraud analytics, such algorithms are useful for detecting anomalies in customer behaviour, to determine whether suspected criminal behaviour is isolated to one or two individuals or whether a group of people are acting in a collusive manner as a fraud ring. Community detection algorithms which are used to detect distinct communities within a larger graph.Currently Haystack includes the following classes of algorithms: ![]() ![]() Graph and machine learning algorithms from Neo4j’s Graph Data Science library. In future we plan to add support for annotation layers, such as GeoJSON shapes, and adding the ability to overlay graph data on top of an image such as a blueprint or a floor plan.Ģ. A geo mode to view elements of the graph on a map, giving a new perspective to data. With Haystack we have already implemented a number of rich features and tools, including:ġ. By using Haystack, your investigation becomes much smarter, simpler and clearer, with you being able to identify links and relationships you previously didn’t know existed. There are many use cases for Haystack, but as one example, let’s suppose that you are a lead investigator in an insurance fraud team, and you are investigating a ring of individuals suspected of making fraudulent property insurance claims. When developing the UI we teamed-up with another partner ( Linkurious) leveraging its powerful Ogma Javascript library. To develop Haystack we teamed-up with our global partner Neo4j to provide the graph database and graph algorithm library. Haystack is a graph based investigative platform that leverages the power of graph databases, with advanced visualisations and state-of-the-art graph and machine learning algorithms. I’ve been leading a team of graph experts, data scientists and UX designers to create a new graph-based investigate tool which we’ve code-named Haystack. ![]() The reason for my quietness of late isn’t due to a lack of things to say, but rather due to being busy leading and developing a new graph initiative at Capgemini. It’s been a number of months since my last blog on graph based Christmas puzzles – I hope you enjoyed it, as I certainly had fun writing it. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |