Systems and methods for updating labels assigned to electronic activities

• US 10,489,462 B1
• Filed: 04/29/2019
• 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, Wulf, John, Prakash, Sathya Hariesh, Brunets, Yurii, Joseph, Rajit Kurien
• Primary Examiner(s): Gofman, Alex
• Application Number:
  US16/398,153
• Publication Number:
  US 20190361941A1
• Time in Patent Office: 211 Days
• Field of Search: None
• 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 a method for updating labels assigned to electronic activities. The method includes accessing electronic activities transmitted or received via electronic accounts associated with data source providers. The node profiles can be updated using the electronic activities. The method includes matching one of the electronic activities to participant node profiles, each corresponds to one of the electronic accounts via which the electronic activity is transmitted or received. The method includes assigning tags to the electronic activity based on the participant node profiles. The method includes detecting a change to the participant node profiles. The method includes determining whether to update the tags assigned to the electronic activity based on the detected change to the participant node profile. The method includes modifying the tag assigned to the electronic activity responsive to determining to update the tag in accordance with the detected change.

Claims

1. A method, comprising:

accessing, by one or more processors, data from a plurality of electronic activities transmitted or received via electronic accounts associated with a plurality of data source providers, the one or more processors maintaining a plurality of node profiles and configured to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including one or more field-value pairs, each field-value pair of the node profile associated with a corresponding field and a field value;

matching, by the one or more processors, a first electronic activity of the plurality of electronic activities to one or more participant node profiles of the plurality of node profiles, each participant node profile corresponding to a respective one of the electronic accounts via which the electronic activity is transmitted or received;

assigning, by the one or more processors, one or more tags to the first electronic activity based on at least one participant node profile of the one or more participant node profiles matched to the first electronic activity;

accessing, by the one or more processors, data from a second electronic activity transmitted or received via one or more of the electronic accounts associated with at least one of the plurality of data source providers;

matching, by the one or more processors, the second electronic activity to the at least one participant node profile;

causing, by the one or more processors, a change to the at least one participant node profile responsive to matching the second electronic activity to the at least one participant node profile, the change to the at least one participant node profile including at least one of i) an addition of a value of a field of the at least one participant node profile, ii) an addition of an indication of an electronic activity to a value data structure of the value of the field of the at least one participant node profile, or iii) a change to a connection profile between the at least one participant node profile and a second node profile;

detecting, by the one or more processors, the change to the at least one participant node profile;

determining, by the one or more processors, whether to assign a second tag to the first electronic activity responsive to determining that a first confidence score of the value satisfies a first threshold score or remove at least one tag of the one or more tags assigned to the first electronic activity responsive to determining that the first confidence score of the value no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score; and

assigning, by the one or more processors, the second tag to the first electronic activity responsive to determining that the first confidence score of the value satisfies the first threshold score;

or

removing, by the one or more processors, the at least one tag assigned to the first electronic activity responsive to determining that the first confidence score no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score.

2. The method of claim 1, further comprising:

determining a connection type between a first participant node profile and a second participant node profile of the participant node profiles;

wherein assigning further comprises assigning the one or more tags to the first electronic activity based on the determined connection type; and

wherein detecting the change further comprises detecting the change to the connection type between the first participant node profile and the second participant node profile of the first electronic activity.

3. The method of claim 1, wherein accessing the plurality of node profiles further comprises accessing the plurality of node profiles representing a plurality of nodes in a node graph, the node graph comprising the plurality of nodes linked to one another via a plurality of edges, each edge of the node graph specifying a relationship between a pair of the plurality of nodes;

wherein detecting the change further comprises detecting the change including an addition of a new relationship between at least one pair of the participant nodes specified by at least one edge of the node graph; and

wherein assigning the second tag or removing the at least one tag further comprises assigning the second tag or removing the at least one tag based on the addition of the existing relationship between the at least one pair of the participant node profiles in the node graph.

4. The method of claim 1,

wherein detecting the change further comprises detecting the change including an addition of a new node field-value pair to the one or more node field-value pairs of the at least one participant node profile;

and

wherein modifying the at least one tag further comprises modifying the at least one tag assigned to the first electronic activity based on the addition of the new node field-value pair to the one or more node field-value pairs of the at least one participant node profile.

5. The method of claim 1, further comprising:

identifying, by the one or more processors responsive to detecting the change to the at least one participant node profile, the first electronic activity that is matched with the at least one participant node profile corresponding to one of the electronic accounts; and

identifying, by the one or more processors, the one or more tags assigned to the first electronic activity; and

wherein determining whether to update the at least one tag further comprises determining whether to update the at least one tag based on the change to the at least one participant node profile.

6. The method of claim 1, wherein the change to the at least one participant node profile includes an addition of the value of the field of the participant node profile or an addition of an indication of the first electronic activity to the value data structure of the value of the field of the participant node profile.

7. The method of claim 1, further comprising

identifying, by the one or more processors, from the plurality of electronic activities, a subset of electronic activities assigned with the at least one tag generated using the field-value pair of the at least one participant node profile;

and

wherein removing further comprises removing the at least one tag assigned to the subset of electronic activities.

8. A system, comprising:

one or more processors coupled to memory, configured to;

access data from a plurality of electronic activities transmitted or received via electronic accounts associated with a plurality of data source providers, the one or more processors maintaining a plurality of node profiles and configured to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including one or more field-value pairs, each field-value pair of the node profile associated with a corresponding field and a field value;

match, by the one or more processors, a first electronic activity of the plurality of electronic activities to one or more participant node profiles of the plurality of node profiles, each participant node profile corresponding to a respective one of the electronic accounts via which the electronic activity is transmitted or received;

assign one or more tags to the first electronic activity based on at least one participant node profile of the one or more participant node profiles matched to the first electronic activity;

access data from a second electronic activity transmitted or received via one or more of the electronic accounts associated with at least one of the plurality of data source providers;

match the second electronic activity to the at least one participant node profile;

cause a change to the at least one participant node profile responsive to matching the second electronic activity to the at least one participant node profile, the change to the at least one participant node profile including at least one of i) an addition of a value of a field of the at least one participant node profile, ii) an addition of an indication of an electronic activity to a value data structure of the value of the field of the at least one participant node profile, or iii) a change to a connection profile between the at least one participant node profile and a second node profile;

detect the change to the at least one participant node profile;

determine whether to assign a second tag to the first electronic activity responsive to determining that a first confidence score of the value satisfies a first threshold score or remove at least one tag of the one or more tags assigned to the first electronic activity responsive to determining that the first confidence score of the value no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score; and

assign the second tag to the first electronic activity responsive to determining that the first confidence score of the value satisfies the first threshold score;

or

remove the at least one tag assigned to the first electronic activity responsive to determining that the first confidence score no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score.

9. The system of claim 8, wherein the one or more processors are further configured to:

determine a connection type between a first participant node profile and a second participant node profile of the participant node profiles;

assign the one or more tags to the first electronic activity based on the determined connection type; and

detect the change to the connection type between the first participant node profile and the second participant node profile of the electronic activity.

10. The system of claim 8, wherein the one or more processors are further configured to:

access the plurality of node profiles representing a plurality of nodes in a node graph, the node graph comprising the plurality of node nodes linked to one another via a plurality of edges, each edge of the node graph specifying a relationship between a pair of the plurality of nodes;

detect the change including an addition of a new relationship between at least one pair of the participant node profiles specified by at least one edge of the node graph; and

wherein to assign the second tag or remove the at least one tag comprises to assign the second tag or remove the at least one tag the at least one tag further comprises based on the addition of the existing relationship between the at least one pair of the participant node profiles in the node graph.

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

detect the change including an addition of a new node field-value pair to the one or more node field-value pairs of the at least one participant node profile; and

modify the at least one tag assigned to the first electronic activity based on the addition of the new node field-value pair to the one or more node field-value pairs of the at least one participant node profile.

12. The system of claim 8, wherein the one or more processors are further configured to:

identify, responsive to detecting the change to the at least one participant node profile, the first electronic activity that is matched with the at least one participant node profile corresponding to one of the electronic accounts; and

identify the one or more tags assigned to the first electronic activity; and

determine whether to update the at least one tag based on the change to the at least one participant node profile.

13. The system of claim 8, wherein the change to the at least one participant node profile includes an addition of the value of the field of the participant node profile or an addition of an indication of the first electronic activity to the value data structure of the value of the field of the participant node profile.

14. The system of claim 8, wherein the one or more processors are further configured to:

detect the change in a confidence score of a field-value pair of the at least one participant node profile to satisfy a threshold value;

identify from the plurality of electronic activities, a subset of electronic activities assigned with the at least one tag generated using the field-value pair of the at least one participant node profile; and

remove the at least one tag assigned to the subset of electronic activities.

15. A non-transitory computer-readable storage medium storing instructions that when executed by one or more processors, cause the one or more processors to perform operations comprising:

accessing data from a plurality of electronic activities transmitted or received via electronic accounts associated with a plurality of data source providers, the one or more processors maintaining a plurality of node profiles and configured to update the plurality of node profiles using the plurality of electronic activities, each node profile of the plurality of node profiles including one or more field-value pairs, each field-value pair of the node profile associated with a corresponding field and a field value;

matching a first electronic activity of the plurality of electronic activities to one or more participant node profiles of the plurality of node profiles, each participant node profile corresponding to a respective one of the electronic accounts via which the electronic activity is transmitted or received;

assigning one or more tags to the first electronic activity based on at least one participant node profile of the one or more participant node profiles matched to the first electronic activity;

accessing data from a second electronic activity transmitted or received via one or more of the electronic accounts associated with at least one of the plurality of data source providers;

matching the second electronic activity to the at least one participant node profile;

causing a change to the at least one participant node profile responsive to matching the second electronic activity to the at least one participant node profile, the change to the at least one participant node profile including at least one of i) an addition of a value of a field of the at least one participant node profile, ii) an addition of an indication of an electronic activity to a value data structure of the value of the field of the at least one participant node profile, or iii) a change to a connection profile between the at least one participant node profile and a second node profile;

detecting the change to the at least one participant node profile;

determining whether to assign a second tag to the first electronic activity responsive to determining that a first confidence score of the value satisfies a first threshold score or remove at least one tag of the one or more tags assigned to the first electronic activity responsive to determining that the first confidence score of the value no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score; and

assigning the second tag to the first electronic activity responsive to determining that the first confidence score of the value satisfies the first threshold score;

or

removing the at least one tag assigned to the first electronic activity responsive to determining that the first confidence score no longer satisfies the first threshold score or a second confidence score of the at least one tag no longer satisfies a second threshold score.

16. The non-transient transitory computer-readable storage medium of claim 15, wherein the operations further comprise:

determining a connection type between a first participant node profile and a second participant node profile of the participant node profiles;

assigning the one or more tags to the first electronic activity based on the determined connection type;

detecting the change to the connection type between the first participant node profile and the second participant node profile of the first electronic activity.

17. The non-transitory computer-readable storage medium of claim 15, wherein the operations further comprise:

detecting the change including an addition of a new node field-value pair to the one or more node field-value pairs of the at least one participant node profile; and

wherein assigning the second tag or removing the at least one tag comprises based on the addition of the new node field-value pair to the one or more node field-value pairs of the at least one participant node profile.

18. The non-transitory computer-readable storage medium of claim 15, wherein the operations further comprise:

identifying, from the plurality of electronic activities, a subset of electronic activities assigned with the at least one tag generated using the field-value pair of the at least one participant node profile; and

wherein removing further comprises removing the at least one tag assigned to the subset of electronic activities.