Systems and methods for assigning node profiles to record objects

• US 10,535,031 B2
• Filed: 05/23/2019
• Issued: 01/14/2020
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Rogynskyy, Oleg, Brunets, Yurii, Kysylov, Maksym
• Primary Examiner(s): Wu, Yicun
• Application Number:
  US16/421,256
• Publication Number:
  US 20190362289A1
• Time in Patent Office: 236 Days
• 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
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 16/122 using management policies backup systems G06F11/1446; file migration policies for HSM systems G06F16/185
• CPC Class Codes: G06F 16/1734 Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
• 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
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/221 Column-oriented storage; Management thereof
• CPC Class Codes: G06F 16/2228 Indexing structures
• 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
• CPC Class Codes: G06F 16/2386 : Bulk updating operations data conversion details G06F16/258
• 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
• CPC Class Codes: G06F 16/2457 : with adaptation to user needs
• CPC Class Codes: G06F 16/24575 : using context
• CPC Class Codes: G06F 16/24578 : using ranking
• CPC Class Codes: G06F 16/2477 : Temporal data queries
• CPC Class Codes: G06F 16/254 : Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• 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
• CPC Class Codes: G06F 16/285 : Clustering or classification
• CPC Class Codes: G06F 16/288 : Entity relationship models
• 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 systems and methods for assigning node profiles to record objects. The method includes maintaining a plurality of node profiles. The method includes identifying a record object to which to assign a node profile. The method includes selecting a subset of node profiles that satisfy a node profile selection policy. The method includes generating, for each of the subset of node profiles, a performance profile using electronic activities of the node profiles and one or more object field-value pairs of the record object. The method includes determining, for a first node profile, that a match score between the first node profile and the record object based on the performance profile and one or more object field-value pairs of the record object satisfies a threshold. The method includes storing an association between the first node profile and the record object based on the match score.

Claims

1. A method comprising:

maintaining, by one or more processors, a plurality of node profiles, each node profile including one or more field-value pairs and updated using electronic activities identifying an entity of the node profile;

identifying, by the one or more processors, a first record object to which to assign a node profile, the first record object corresponding to a system of record, the first record object linked to a second record object of the system of record identifying a group entity and a third record object of the system of record identifying a first entity, the first record object comprising one or more field-value pairs including a stage field-value pair having a stage field and a stage value selected from a plurality of stage values, each stage value of the plurality of stage values indicating a respective proximity to a completion of an event corresponding to the first record object;

selecting, by the one or more processors, from the plurality of node profiles, a subset of node profiles that satisfy a node profile selection policy;

generating, by the one or more processors, for each node profile of the subset of node profiles, a performance profile using the electronic activities identifying the respective entity corresponding to the node profile and the one or more object field-value pairs of the first record object;

determining, by the one or more processors, for a first node profile of the subset, that a match score between the first node profile and the first record object based on the performance profile and one or more object field-value pairs of the first record object satisfies a threshold; and

storing, by the one or more processors, an association between the first node profile of the subset and the first record object based on the match score.

2. The method of claim 1, wherein determining, for the first node profile of the subset, that the match score between the first node profile and the first record object satisfies the threshold further comprising:

determining, by the one or more processors, for each node profile of the subset, a respective match score between the node profile and the first record object based on the performance profile of the node profile and the one or more object field-value pairs of the first record object; and

determining, by the one or more processors, that the match score between the first node profile and the first record object is greater than respective match scores between remaining node profiles of the subset and the first record object.

3. The method of claim 1, wherein selecting the subset of node profiles, by the one or more processors, using the node profile selection policy, further comprises:

identifying a data source provider of a system of record of the record object;

identifying a group entity corresponding to the data source provider; and

selecting the subset of node profiles to include one or more node profiles that identify the group entity in a field-value pair of the respective node profile.

4. The method of claim 1, wherein the performance profile of the entity includes an availability metric for the entity, wherein the method further comprises:

identifying, by the one or more processors, one or more record objects to which the entity is linked;

determining, by the one or more processors, for each record object, a current stage of the record object; and

generating, by the one or more processors, based on the current stages of the one or more record objects, the availability metric of the entity.

5. The method of claim 1, wherein the performance profile of the entity includes an availability metric for the entity, wherein the method further comprises:

determining, by the one or more processors, the availability metric representing a number of actions to be performed by the entity within a predetermined time period using at least one of i) record objects to which the entity is linked;

ii) electronic activities the entity is expected to generate;

or iii) electronic activities scheduled within the predetermined time period.

6. The method of claim 5, wherein the first record object is an account record object, the method further comprising:

identifying, by the one or more processors, connection profiles between the entity and one or more member entities linked with a group entity of the account record object; and

wherein generating the performance profile comprises generating the performance profile based on the identified connection profiles and the availability metric.

7. The method of claim 1, wherein the first record object is an account record object, the method further comprising:

identifying, by the one or more processors, connection profiles between the entity and one or more member entities linked with the group entity of the account record object; and

wherein generating the performance profile comprises generating the performance profile based on the identified connection profiles.

8. The method of claim 1, wherein the first record object is a lead record object, the method further comprising:

matching, by the one or more processors, the lead record object to a node profile of the plurality of node profiles;

extracting, by the one or more processors, one or more field-value pairs of the node profile; and

generating the match score between the first node profile and the lead record object comprises comparing field-value pairs of the node profile of the lead record object with field-value pairs of second node profiles of second lead record objects previously associated with the first node profile.

9. The method of claim 8, wherein the one or more field-value pairs corresponds to a first field identifying a seniority of the entity of the lead record object and a second field identifying a department of the entity of the lead record object.

10. The method of claim 1, wherein the first record object is linked with one or more second member entities of the group entity of the first node profile and further comprising:

determining, for the first node profile, a first set of record objects with which a first entity of the first node profile is linked;

identifying, by the one or more processors, from the first set of record objects, a number of record objects with which the one or more second entities and the first entity are linked; and

generating the match score between the first node profile and the first record object comprises based on the number of record objects with which the one or more second entities and the first entity are linked.

11. A system comprising:

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

maintain a plurality of node profiles, each node profile including one or mom field-value pairs and updated using electronic activities identifying an entity of the node profile;

identify a record object to which to assign a node profile, the first record object corresponding to a system of record, the first record object linked to a second record object of the system of record identifying a group entity and a third record object of the system of record identifying a first entity, the first record object comprising one or more field-value pairs including a stage field-value pair having a stage field and a stage value selected from a plurality of stage values, each stage value of the plurality of stage values indicating a respective proximity to a completion of an event corresponding to the first record object;

select, from the plurality of node profiles, a subset of node profiles that satisfy a node profile selection policy;

generate, for each node profile of the subset of node profiles, a performance profile using the electronic activities identifying the respective entity

corresponding to the node profile

and the one or more object field-value pairs of the first record object;

determine, for a first node profile of the subset, that a match score between the first node profile and the first record object based on the performance profile and one or more object field-value pairs of the first record object satisfies a threshold; and

store, an association between the first node profile of the subset and the first record object based on the match score.

12. The system of claim 11, wherein the one or more processors are further configured to:

determine, for each node profile of the subset, a respective match score between the node profile and the first record object based on the performance profile of the node profile and the one or more object field-value pairs of the first record object; and

determine that the match score between the first node profile and the first record object is greater than respective match scores between remaining node profiles of the subset and the first record object.

13. The system of claim 11, wherein the one or more processors are further configured to:

identify a data source provider of a system of record of the first record object;

identify a group entity corresponding to the data source provider; and

select the subset of node profiles to include one or more node profiles that identify the group entity in a field-value pair of the respective node profile.

14. The system of claim 11, wherein the performance profile of the entity includes an availability metric for the entity and the one or more processors are further configured to:

identify one or more record objects to which the entity is linked;

determine, for each record object, a current stage of the record object; and

generate based on the current stages of the one or more record objects, the availability metric of the entity.

15. The system of claim 11, wherein the performance profile of the entity includes an availability metric for the entity and the one or more processors are further configured to:

determine the availability metric representing a number of actions to be performed by the entity within a predetermined time period using at least one of i) record objects to which the entity is linked;

ii) electronic activities the entity is expected to generate;

or iii) electronic activities scheduled within the predetermined time period.

16. The system of claim 15, wherein the first record object is an account record object and the one or more processors are further configured to:

identify connection profiles between the entity and one or more member entities linked with a group entity of the account record object; and

generate the performance profile based on the identified connection profiles and the availability metric.

17. The system of claim 11, wherein the first record object is an account record object and the one or more processors are further configured to:

identify connection profiles between the entity and one or more member entities linked with the group entity of the account record object; and

generate the performance profile based on the identified connection profiles.

18. The system of claim 11, wherein the first object is a lead record object and the one or more processors are further configured to:

match the lead record object to a node profile of the plurality of node profiles;

extract one or more field-value pairs of the node profile; and

compare field-value pairs of the node profile of the lead record object with field-value pairs of second node profiles of second lead record objects previously associated with the first node profile.

19. The system of claim 18, wherein the one or more field-value pairs corresponds to a first field identifying a seniority of the entity of the lead record object and a second field identifying a department of the entity of the lead record object.

20. 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:

maintaining, by one or more processors, a plurality of node profiles, each node profile including one or more field-value pairs and updated using electronic activities identifying an entity of the node profile;

identifying, by the one or more processors, a first record object to which to assign a node profile, the first record object corresponding to a system of record, the first record object linked to a second record object of the system of record identifying a group entity and a third record object of the system of record identifying a first entity, the first record object comprising one or more field-value pairs including a stage field-value pair having a stage field and a stage value selected from a plurality of stage values, each stage value of the plurality of stage values indicating a respective proximity to a completion of an event corresponding to the first record object;

selecting, by the one or more processors, from the plurality of node profiles, a subset of node profiles that satisfy a node profile selection policy;

generating, by the one or more processors, for each node profile of the subset of node profiles, a performance profile using the electronic activities identifying the respective entity corresponding to the node profile and the one or more object field-value pairs of the first record object;

determining, by the one or more processors, for a first node profile of the subset, that a match score between the first node profile and the first record object based on the performance profile and one or more object field-value pairs of the first record object satisfies a threshold; and

storing, by the one or more processors, an association between the first node profile of the subset and the first record object based on the match score.