Systems and methods for updating record objects of tenant systems of record based on a change to a corresponding record object of a master system of record

• US 10,489,388 B1
• Filed: 04/30/2019
• Issued: 11/26/2019
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Rogynskyy, Oleg, Jain, Vardhman, Joseph, Rajit Kurien, Navarro, Jose Alberto Muniz, Brunets, Yurii
• Primary Examiner(s): Le, Uyen T
• Application Number:
  US16/400,000
• Publication Number:
  US 20190361876A1
• Time in Patent Office: 210 Days
• Field of Search: 707736
• CPC Class Codes: G06F 11/3024 where the computing system component is a central processing unit [CPU]
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
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• CPC Class Codes: G06F 16/178 Techniques for file synchronisation in file systems
• CPC Class Codes: G06F 16/182 Distributed file systems
• CPC Class Codes: G06F 16/212 with details for data modelling support
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/219 Managing data history or versioning querying versioned data G06F16/2474; querying temporal data G06F16/2477
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• CPC Class Codes: G06F 16/221 Column-oriented storage; Management thereof
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• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 16/2272 Management thereof
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/235 Update request formulation
• CPC Class Codes: G06F 16/2358 Change logging, detection, and notification replication G06F16/27
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
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• CPC Class Codes: G06F 16/245 : Query processing
• CPC Class Codes: G06F 16/24558 : Binary matching operations
• CPC Class Codes: G06F 16/24564 : Applying rules; Deductive queries
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• CPC Class Codes: G06F 16/2477 : Temporal data queries
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• CPC Class Codes: G06F 16/256 : in federated or virtual databases
• CPC Class Codes: G06F 16/26 : Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/27 : Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/273 : Asynchronous replication or reconciliation
• CPC Class Codes: G06F 16/28 : Databases characterised by their database models, e.g. relational or object models
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• CPC Class Codes: G06F 16/289 : Object oriented databases
• CPC Class Codes: G06F 16/29 : Geographical information databases
• CPC Class Codes: G06F 16/313 : Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/337 : Profile generation, learning or modification
• CPC Class Codes: G06F 16/355 : Class or cluster creation or modification
• CPC Class Codes: G06F 16/901 : Indexing; Data structures therefor; Storage structures for retrieval from the web G06F16/951
• CPC Class Codes: G06F 16/9024 : Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/90344 : by using string matching techniques
• CPC Class Codes: G06F 16/9035 : Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/906 : Clustering; Classification
• CPC Class Codes: G06F 16/93 : Document management systems
• CPC Class Codes: G06F 16/9535 : Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 21/6218 : to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6245 : Protecting personal data, e.g. for financial or medical purposes
• CPC Class Codes: G06F 40/20 : Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/205 : Parsing
• CPC Class Codes: G06F 40/237 : Lexical tools
• CPC Class Codes: G06F 40/295 : Named entity recognition
• CPC Class Codes: G06F 40/30 : Semantic analysis
• CPC Class Codes: G06F 7/14 : Merging, i.e. combining at least two sets of record carriers each arranged in the same ordered sequence to produce a single set having the same ordered sequence
• CPC Class Codes: G06F 9/542 : Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 3/08 : Learning methods
• CPC Class Codes: G06N 5/022 : Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/025 : Extracting rules from data
• CPC Class Codes: G06N 5/04 : Inference or reasoning models
• CPC Class Codes: G06N 7/02 : using fuzzy logic computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00
• CPC Class Codes: G06Q 10/04 : Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/063114 : Status monitoring or status determination for a person or group
• CPC Class Codes: G06Q 10/06312 : Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06315 : Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06393 : Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/06398 : Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/10 : Office automation; Time management
• CPC Class Codes: G06Q 10/107 : Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06Q 10/109 : Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 10/1091 : Recording time for administrative or management purposes
• CPC Class Codes: G06Q 10/1095 : Meeting or appointment
• CPC Class Codes: G06Q 30/0201 : Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06Q 50/22 : Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: H04L 12/14 : Charging , metering or billing arrangements for data wireline or wireless communications
• CPC Class Codes: H04L 12/1407 : Policy-and-charging control [PCC] architecture
• CPC Class Codes: H04L 12/1831 : Tracking arrangements for later retrieval, e.g. recording contents, participants activities or behavior, network status
• CPC Class Codes: H04L 2101/00 : Indexing scheme associated with group H04L61/00
• CPC Class Codes: H04L 2101/35 : containing special prefixes
• CPC Class Codes: H04L 2101/37 : E-mail addresses
• CPC Class Codes: H04L 41/082 : the condition being updates or upgrades of network functionality
• CPC Class Codes: H04L 41/14 : Network analysis or design
• CPC Class Codes: H04L 43/026 : using flow identification
• CPC Class Codes: H04L 43/045 : for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/062 : related to network traffic
• CPC Class Codes: H04L 43/065 : related to network devices
• CPC Class Codes: H04L 43/067 : using time frame reporting
• CPC Class Codes: H04L 43/08 : Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 43/0876 : Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/14 : using software, i.e. software packages network security related monitoring H04L63/1408
• CPC Class Codes: H04L 51/046 : Interoperability with other network applications or services
• CPC Class Codes: H04L 51/212 : using filtering or selective blocking
• CPC Class Codes: H04L 51/234 : for tracking messages
• CPC Class Codes: H04L 51/42 : Mailbox-related aspects, e.g. synchronisation of mailboxes
• CPC Class Codes: H04L 61/45 : Network directories; Name-to-address mapping
• CPC Class Codes: H04L 61/4594 : Address books, i.e. directories containing contact information about correspondents telephone directories in user terminals H04M1/27453
• CPC Class Codes: H04L 67/125 : involving control of end-device applications over a network
• CPC Class Codes: H04L 67/30 : Profiles
• CPC Class Codes: H04L 67/303 : Terminal profiles
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04M 15/00 : Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
• CPC Class Codes: H04M 15/41 : Billing record details, i.e. parameters, identifiers, structure of call data record [CDR]
• CPC Class Codes: H04M 15/50 : for cross-charging network operators
• CPC Class Codes: H04M 15/58 : based on statistics of usage or network monitoring
• CPC Class Codes: H04M 15/60 : based on actual use of network resources
• CPC Class Codes: H04M 15/66 : Policy and charging system
• CPC Class Codes: H04M 15/755 : Account identification
• CPC Class Codes: H04M 2203/556 : Statistical analysis and interpretation
• CPC Class Codes: H04M 3/2218 : Call detail recording
• CPC Class Codes: H04M 3/436 : Arrangements for screening incoming calls , i.e. evaluating the characteristics of a call before deciding whether to answer it based on the calling party profile H04M3/42059; based on location H04M3/42348; based on presence H04M3/42365; diversion H04M3/54
• CPC Class Codes: H04M 3/5175 : Call or contact centers supervision arrangements
• CPC Class Codes: H04M 3/56 : Arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities video conference systems H04N7/15
• CPC Class Codes: H04W 4/24 : Accounting or billing

Abstract

The present disclosure relates to updating record objects of tenant systems of record based on a change to a corresponding record object of a master system of record. A method can include identifying a first record object from a first system of record including record objects generated using second systems of record of a plurality of data source providers. The method can include determining an update to a first object field-value pair of the first record object of the first system of record. The method can include identifying a plurality of second record objects of the second systems of record that are linked to the first record object of the first system of record. The method can include updating at least one second record object by changing a value of an existing object field-value pair of the at least one second record object or adding a new object field-value pair to the at least one second record object.

Claims

1. A method comprising:

identifying, by one or more processors, a first record object from a first system of record including a plurality of record objects generated using data from a plurality of second record objects of a plurality of second systems of record of a plurality of data source providers, each second system of record maintained by a respective data source provider of the plurality of data source providers, the first system of record maintained by the one or more processors;

generating, by the one or more processors, for each second record object of the plurality of second record objects of the plurality of second systems of record, a corresponding shadow record object including one or more object field-value pairs matching corresponding object field-value pairs of the second record object, each shadow record object maintained by the one or more processors;

determining, by the one or more processors, an update to a first object field-value pair of the first record object of the first system of record;

identifying, by the one or more processors, a plurality of shadow record objects that are associated with the first record object of the first system of record, each shadow record object including at least one object field-value pair that matches a corresponding object field-value pair of the first record object; and

updating, by the one or more processors, at least one shadow record object of the plurality of shadow record objects by changing a value of an existing object field-value pair of the at least one shadow record object or adding a new object field-value pair to the at least one shadow record object.

2. The method of claim 1, wherein identifying the plurality of shadow record objects that are associated with the first record object of the first system of record further comprises:

for each shadow record object of the plurality of shadow record objects;

accessing, by the one or more processors, one or more data structures storing associations between the plurality of record objects of the first system of record and record objects of the shadow systems of record;

identifying, by the one or more processors, at least one entry of the one or more data structures corresponding to the first record object of the first system of record; and

identifying, by the one or more processors, the plurality of shadow record objects based on information included in the at least one entry of the one or more data structures.

3. The method of claim 2, wherein:

the first record object of the first system of record includes a plurality of fields, each field of the plurality of fields including one or more value data structures, each value data structure of the one or more value data structures identifying a value and one or more entries corresponding to respective one or more shadow record objects that includes an object field-value pair that matches the field-value pairs of the first record object corresponding to the value data structure.

4. The method of claim 1, wherein identifying the plurality of shadow record objects that are associated with the first record object of the first system of record further comprises:

for each shadow record object of the plurality of shadow record objects;

comparing, by the one or more processors, the object field-value pairs of the shadow record object with corresponding object field-value pairs of the first record object; and

determining, by the one or more processors, responsive to the comparison, that the shadow record object matches the first record object in accordance with a record object matching policy.

5. The method of claim 1, wherein at least one of the second systems of record is maintained by a respective one of the data source providers, and the method further comprising

updating at least one second record object associated with the corresponding at least one shadow record object further comprises transmitting, by the one or more processors to the respective one of the data source providers, an instruction corresponding to the update to the object field-value pair of the first record object.

6. The method of claim 1, further comprising:

accessing, by the one or more processors, an electronic activity transmitted or received by an electronic account associated with one of the data source providers;

extracting, by the one or more processors, a plurality of activity field-value pairs from the electronic activity;

matching, by the one or more processors, the electronic activity to a corresponding record object of at least one second system of record of the plurality of second systems of record based on the activity field-value pairs;

updating, by the one or more processors, an object field-value pair of the corresponding record object of the at least one second system of record based on determining that the object field-value pair does not match a corresponding activity field-value pair of the electronic activity; and

updating, by the one or more processors, an object field-value pair of the corresponding record object of the first system of record.

7. The method of claim 1, further comprising:

accessing, by the one or more processors, an electronic activity transmitted or received by an electronic account associated with one of the data source providers;

extracting, by the one or more processors, a plurality of electronic activity field-value pairs from the electronic activity;

comparing, by the one or more processors, the electronic activity field-value pairs of the electronic activity with corresponding node field-value pairs of a plurality of node profiles maintained by the one or more processors;

determining, by the one or more processors, responsive to the comparison, that a first node profile of the plurality of node profiles matches the first record object in accordance with a record object matching policy; and

generating, by the one or more processors, a new node field-value pair of the first node profile based on determining that the activity field-value pair of the electronic activity does not match any existing node field-value pairs of the node profile.

8. The method of claim 7, further comprising:

identifying, by the one or more processors, the first record object of the first system of record to update based on the first node profile; and

updating, by the one or more processors, an object field-value pair of the first record object corresponding to the first node field-value pair of the first node profile based on determining that the object field-value pair does not match the first node field-value pair of the first node profile.

9. The method of claim 1, further comprising:

accessing, by the one or more processors, a third system of record not included in the plurality of second systems of record;

identifying a record object of the third system of record corresponding to the first record object;

identifying an object field-value pair of the third record object that does not match a corresponding object field-value pair of the first record object; and

generating a new object field-value pair in the first record object that matches the object field-value pair of the third record object.

10. The method of claim 9, further comprising:

determining a confidence score of the value of the new object field-value pair; and

determining that the confidence score satisfies a predetermined threshold; and

wherein updating the at least one shadow record object of the plurality of shadow record objects further comprises updating the at least one shadow record object responsive to determining that the confidence score satisfies a predetermined threshold.

11. The method of claim 1, further comprising:

identifying, by the one or more processors, a third system of record not included in the plurality of second systems of record;

determining, by the one or more processors, a setting to allow use of the third system of record by the one or more processors to update at least one of the plurality of second systems of record; and

storing, by the one or more processors in one or more data structures, information corresponding to the setting to allow use of the third system of record by the one or more processors to update the at least one of the plurality of second systems of record.

12. The method of claim 1, further comprising:

identifying, by the one or more processors, a first data source provider of the plurality of data source providers associated with the first record object;

determining, by the one or more processors, at least one second system of record of the plurality of second systems of record that corresponds to the first data source provider; and

transmitting, by the one or more processors, an instruction to cause the at least one second system of record to update at least one record object.

13. The method of claim 1, further comprising:

identifying, by the one or more processors, a third system of record not included in the plurality of second systems of record;

determining, by the one or more processors, a restriction setting to restrict use of the third system of record to update the first system of record; and

storing, by the one or more processors in one or more data structures, information corresponding to the restriction setting to restrict use of the third system of record to update the first system of record.

14. The method of claim 1, further comprising:

identifying, by the one or more processors, a third system of record not included in the plurality of second systems of record;

determining, by the one or more processors, a setting to allow use of the third system of record to update the first system of record; and

storing, by the one or more processors in one or more data structures, information corresponding to the setting to allow use of the third system of record to update the first system of record.

15. A non transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by one or more processors to perform a method comprising:

identifying a first record object from a first system of record including a plurality of record objects generated using data from a plurality of second record objects of a plurality of second systems of record of a plurality of data source providers, each second system of record maintained by a respective data source provider of the plurality of data source providers, the first system of record maintained by the one or more processors;

generating, for each second record object of the plurality of second record objects of the plurality of second systems of record, a corresponding shadow record object including one or more object field-value pairs matching corresponding object field-value pairs of the second record object, each shadow record object maintained by the one or more processors;

determining an update to a first object field-value pair of the first record object of the first system of record;

identifying a plurality of shadow record objects that are associated with the first record object of the first system of record, each shadow record object including at least one object field-value pair that matches a corresponding object field-value pair of the first record object; and

updating at least one shadow record object of the plurality of shadow record objects by changing a value of an existing object field-value pair of the at least one shadow record object or adding a new object field-value pair to the at least one shadow record object.

16. A system comprising:

one or more hardware processors configured by machine-readable instructions to;

identify a first record object from a first system of record including a plurality of record objects generated using data from a plurality of second record objects of a plurality of second systems of record of a plurality of data source providers, each second system of record maintained by a respective data source provider of the plurality of data source providers, the first system of record maintained by the one or more hardware processors;

generate for each second record object of the plurality of second record objects of the plurality of second systems of record, a corresponding shadow record object including one or more object field-value pairs matching corresponding object field-value pairs of the second record object, each shadow record object maintained by the one or more hardware processors;

determine an update to a first object field-value pair of the first record object of the first system of record;

identify a plurality of shadow record objects that are associated with the first record object of the first system of record, each shadow record object including at least one object field-value pair that matches a corresponding object field-value pair of the first record object; and

update at least one shadow record object of the plurality of shadow record objects by changing a value of an existing object field-value pair of the at least one shadow record object or adding a new object field-value pair to the at least one shadow record object.

17. The system of claim 16, wherein the one or more hardware processors are further configured by the machine readable instructions to the plurality of shadow record objects that are associated with the first record object of the first system of record by:

for each shadow record object of the plurality of shadow record objects;

accessing one or more data structures storing associations between the plurality of record objects of the first system of record and record objects of the shadow systems of record;

identifying at least one entry of the one or more data structures corresponding to the first record object of the first system of record; and

identifying the plurality of shadow record objects based on information included in the at least one entry of the one or more data structures.

18. The system of claim 17, wherein:

the first record object of the first system of record includes a plurality of fields, each field of the plurality of fields including one or more value data structures, each value data structure of the one or more value data structures identifying a value and one or more entries corresponding to respective one or more shadow record objects that includes an object field-value pair that matches the field-value pairs of the first record object corresponding to the value data structure.

19. The system of claim 16, wherein the one or more hardware processors are further configured to identify the plurality of shadow record objects that are associated with the first record object of the first system of record by:

for each shadow record object of the plurality of shadow record objects;

comparing the object field-value pairs of the shadow record object with corresponding object field-value pairs of the first record object; and

determining, responsive to the comparison, that the shadow record object matches the first record object in accordance with a record object matching policy.