SYSTEMS AND METHODS FOR UPDATING MULTIPLE VALUE DATA STRUCTURES USING A SINGLE ELECTRONIC ACTIVITY

• US 20190361884A1
• Filed: 03/21/2019
• Published: 11/28/2019
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Wulf, John, Prakash, Sathya Hariesh, Lutsaievska, Tetiana, Hermanek, Stefan, Kozlov, Heorhiy, Rogynskyy, Oleg
• Granted Patent: US 10,678,795 B2
• Time in Patent Office: 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 updating multiple value data structures using a single electronic activity. Exemplary embodiments may include hardware processors configured by machine-readable instructions to access electronic activities transmitted or received via electronic accounts associated with data source providers; to maintain and update node profiles; to determine a first activity field-value pair and a second activity field-value pair associated with a participant of the first electronic activity; to identify a first node profile of the node profiles that includes a first node field-value pair that matches the first activity field-value pair; to update a first value data structure corresponding to a first value included in the first node field-value pair by adding a first entry to the first value data structure identifying the first electronic activity; and to update a second value data structure corresponding to a second value.

Claims

1. A system comprising:

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

access a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, wherein the one or more hardware processors are further configured to maintain a plurality of node profiles and to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including 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 including a value and one or more entries corresponding to respective one or more data points;

determine from a first electronic activity of the plurality of electronic activities, a first activity field-value pair associated with a participant of the first electronic activity and a second activity field-value pair associated with the participant of the first electronic activity;

identify a first node profile of the plurality of node profiles that includes a first node field-value pair that matches the first activity field-value pair determined from the first electronic activity and a second node field-value pair that matches the second activity field-value pair of the first electronic activity;

update a first value data structure corresponding to a first value included in the first node field-value pair by adding a first entry to the first value data structure identifying the first electronic activity; and

update a second value data structure corresponding to a second value included in the second node field-value pair by adding a second entry to the second value data structure identifying the first electronic activity.

2. The system of claim 1, wherein the participant is a sender of the first electronic activity;

wherein the one or more hardware processors are further configured by the machine-readable instructions to determine from the first electronic activity of the plurality of electronic activities, a third activity field-value pair associated with a recipient of the first electronic activity; and

wherein the one or more hardware processors are further configured by the machine-readable instructions to identify a second node profile of the plurality of node profiles that includes a third node field-value pair that matches the third activity field-value pair determined from the first electronic activity.

3. The system of claim 2, wherein the one or more hardware processors are further configured by the machine-readable instructions to update a third value data structure corresponding to a third value included in the third node field-value pair by adding a third entry to the third value data structure identifying the first electronic activity.

4. The system of claim 1, wherein the one or more hardware processors are further configured by the machine-readable instructions to:

identify a source of the first electronic activity;

determine a contribution score of the first entry of the first value data structure, the contribution score used to determine a confidence score of the value of the first value data structure of the first node profile.

5. The system of claim 4, wherein the one or more hardware processors are further configured by the machine-readable instructions to determine the confidence score of the value of the first value data structure of the first node profile based on the contribution score of the first entry and respective contribution scores of one or more additional entries included in the first value data structure of the first node profile.

6. The system of claim 4, wherein the one or more hardware processors are further configured by the machine-readable instructions to determine the contribution score of the first entry includes determining the contribution score based on a time at which the electronic activity was received.

7. The system of claim 1, wherein:

the first electronic activity comprises an email message;

the first activity field-value pair comprises an email address of the participant of the email message; and

the second activity field-value pair comprises a name of the participant of the email message.

8. The system of claim 7, wherein the one or more hardware processors are further configured by the machine-readable instructions to:

generate, from data included in the first electronic activity, a plurality of activity field-value pairs including the first activity-field pair and the second activity-field pair;

identify a plurality of candidate node profiles including the first node profile by comparing the plurality of activity field-value pairs to respective node field-value pairs of the candidate node profiles;

generate for each candidate node profile, a match score indicating a likelihood that the participant of the first electronic activity corresponds to the candidate node profile based on comparing the plurality of activity field-value pairs to respective node field-value pairs included in the candidate node profile; and

identify the first node profile as corresponding to the participant based on the match score of the first node profile.

9. The system of claim 7, wherein the one or more hardware processors are further configured by the machine-readable instructions to access the plurality of electronic activities by retrieving the email message from a mail server of the data source provider.

10. The system of claim 7, wherein the one or more hardware processors are further configured by the machine-readable instructions to add a new value to a field of the first node profile that does not match the value of the activity-field value pair responsive to determining that an activity field-value pair of the first electronic activity does not have a corresponding match in the first node profile, wherein adding the new value includes adding a new value data structure and adding an entry to the new value data structure identifying the first electronic activity.

11. A method comprising:

accessing, by one or more processors, a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, wherein the one or more processors are configured to maintain a plurality of node profiles and to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including 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 including a value and one or more entries corresponding to respective one or more data points;

determining, by the one or more processors, from a first electronic activity of the plurality of electronic activities, a first activity field-value pair associated with a participant of the first electronic activity and a second activity field-value pair associated with the participant of the first electronic activity;

identifying, by the one or more processors, a first node profile of the plurality of node profiles that includes a first node field-value pair that matches the first activity field-value pair determined from the first electronic activity and a second node field-value pair that matches the second activity field-value pair of the first electronic activity;

updating, by the one or more processors, a first value data structure corresponding to a first value included in the first node field-value pair by adding a first entry to the first value data structure identifying the first electronic activity; and

updating, by the one or more processors, a second value data structure corresponding to a second value included in the second node field-value pair by adding a second entry to the second value data structure identifying the first electronic activity.

12. The method of claim 11, wherein the participant is a sender of the first electronic activity, the method further comprising:

determining, by the one or more processors, from the first electronic activity of the plurality of electronic activities, a third activity field-value pair associated with a recipient of the first electronic activity; and

identifying, by the one or more processors, a second node profile of the plurality of node profiles that includes a third node field-value pair that matches the third activity field-value pair determined from the first electronic activity.

13. The method of claim 12, further comprising updating, by the one or more processors, a third value data structure corresponding to a third value included in the third node field-value pair by adding a third entry to the third value data structure identifying the first electronic activity.

14. The method of claim 11, further comprising:

identifying, by the one or more processors, a source of the first electronic activity; and

determining, by the one or more processors, a contribution score of the first entry of the first value data structure, the contribution score used to determine a confidence score of the value of the first value data structure of the first node profile.

15. The method of claim 14, further comprising determining, by the one or more processors, the confidence score of the value of the first value data structure of the first node profile based on the contribution score of the first entry and respective contribution scores of one or more additional entries included in the first value data structure of the first node profile.

16. The method of claim 14, wherein determining the contribution score of the first entry includes determining, by the one or more processors, the contribution score based on a time at which the electronic activity was received.

17. The method of claim 11, wherein:

the first electronic activity comprises an email message;

the first activity field-value pair comprises an email address of the participant of the email message; and

the second activity field-value pair comprises a name of the participant of the email message.

18. The method of claim 17, further comprising:

generating, by the one or more processors, from data included in the first electronic activity, a plurality of activity field-value pairs including the first activity-field pair and the second activity-field pair;

identifying, by the one or more processors, a plurality of candidate node profiles including the first node profile by comparing the plurality of activity field-value pairs to respective node field-value pairs of the candidate node profiles;

generating, by the one or more processors, for each candidate node profile, a match score indicating a likelihood that the participant of the first electronic activity corresponds to the candidate node profile based on comparing the plurality of activity field-value pairs to respective node field-value pairs included in the candidate node profile; and

identifying, by the one or more processors, the first node profile as corresponding to the participant based on the match score of the first node profile.

19. The method of claim 17, wherein accessing, by the one or more processors, the plurality of electronic activities further comprises retrieving the email message from a mail server of the data source provider.

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

accessing a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers, wherein the one or more processors are configured to maintain a plurality of node profiles and to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including 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 including a value and one or more entries corresponding to respective one or more data points;

determining from a first electronic activity of the plurality of electronic activities, a first activity field-value pair associated with a participant of the first electronic activity and a second activity field-value pair associated with the participant of the first electronic activity;

identifying a first node profile of the plurality of node profiles that includes a first node field-value pair that matches the first activity field-value pair determined from the first electronic activity and a second node field-value pair that matches the second activity field-value pair of the first electronic activity;

updating a first value data structure corresponding to a first value included in the first node field-value pair by adding a first entry to the first value data structure identifying the first electronic activity; and

updating a second value data structure corresponding to a second value included in the second node field-value pair by adding a second entry to the second value data structure identifying the first electronic activity.