Dear all, I am trying to use neo4j for anomaly detection in mobile network data (CDRs). This means that I am trying to detect abnormal customers behavior. The format of the records may change from company to company but the most common attributes are: • Caller and called Identification Number; • Date and time; • Type of Service (Voice Call, SMS, etc...) ; • Duration; • Network access point identifiers; • Others;
I am trying to model such data using Neo4j and then use cypher queries to detect abnormal customers behaviors Have any one seen or worked with a similar example? examples of the scenarios that I am interested in are 1- a call which is very long 2- what are the access points which are used by more users compared to the other access points? 3- Detect Simbox or interconnect Bypass fraud. How to knows whether the call is normal call or Simbox? 4- a phone number (a) which call another phone number (b) more that (x) times every day? Kind regards -- You received this message because you are subscribed to the Google Groups "Neo4j" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
