Almost there. On Mon, Mar 27, 2017 at 11:33 PM, Fares <emsai...@gmail.com> wrote:
> Hi, > > Have you published that work so that I could go through it! > > > On Monday, February 6, 2017 at 4:39:34 AM UTC+3, Kamal Murthy wrote: >> >> Hi, >> >> I Developed a graph model (with time series) from a relational model to >> store call detail records (CDR) in nodes, relationships and properties. >> Developed Cypher queries to identify calls that were answered, abandoned, >> sent to voice mail direct etc., and produced tabular data. Identified the >> telephone numbers that never answered the incoming calls along with other >> metrics. >> >> -Kamal >> >> >> On Tuesday, November 1, 2016 at 3:18:20 AM UTC-7, Michael Hunger wrote: >>> >>> Hey, >>> >>> we've done a large scale CDR project at a major Telco company. That one >>> was mostly around accounting and recommendations. >>> >>> Fraud detection would require a different model, but my colleague who >>> worked on that said if you're interested, feel free to contact us >>> officially <https://neo4j.com/contact-us/> for a discussion / >>> evaluation. >>> >>> In general i would take the entities you mentioned and the questions >>> you're asking and draw the whiteboard model that allows you easily to >>> answer the questions. >>> Then take a months worth of data and import it into the model. The >>> cypher queries should mostly look like "query by example" on your model >>> structure with some aggregation and ranking. >>> >>> Michael >>> >>> On Sun, Oct 30, 2016 at 3:11 PM, Craig Taverner <cr...@amanzi.com> >>> wrote: >>> >>>> In my previous work I did data modeling of telecoms networks, including >>>> modeling various event log data (including CDR data), and building >>>> statistics trees on the event logs for later querying. Take a look at the >>>> presentation I gave at graphconnect NY 2013 for some ideas of what we did: >>>> >>>> - Slides: http://www.slideshare.net/craigtaverner/modeling-in- >>>> telecoms-2013 (especially slides 27-29 & 32-33) >>>> - Video: https://vimeo.com/79390660 >>>> >>>> While you could just import a CDR log as a long chain of events, what >>>> you want to do is connect events into category trees, or time trees, or >>>> some other graph structure, at load time (the trees should be built while >>>> importing the data), leading to the possiblity to write Cypher queries that >>>> simply ask pattern questions (match the trees) to get the answers you want. >>>> Some obvious examples from the above: >>>> >>>> - Connect calls from specific phones to 'phone nodes' (do the same >>>> for both caller and callee, see slide 32). >>>> - If you have large volumes of data, consider intermediate nodes >>>> (for example if you always ask about specific phones within time ranges, >>>> then make intermediate nodes time-phone nodes, eg. a single node for >>>> each >>>> phone on each day/date). >>>> - A time tree for time range queries (eg. the very long call query >>>> above). >>>> >>>> I cannot comment on 'simbox' because I don't know what that means. >>>> Watch the video and see if you get ideas on how to model it yourself, >>>> otherwise ask again. >>>> >>>> >>>> >>>> On Sat, Oct 29, 2016 at 4:41 PM, Fares <emsa...@gmail.com> wrote: >>>> >>>>> 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 neo4j+un...@googlegroups.com. >>>>> For more options, visit https://groups.google.com/d/optout. >>>>> >>>> >>>> -- >>>> 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 neo4j+un...@googlegroups.com. >>>> For more options, visit https://groups.google.com/d/optout. >>>> >>> >>> -- > 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 neo4j+unsubscr...@googlegroups.com. > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "Neo4j" group. 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