Systems and methods for assigning labels based on matching electronic activities to record objects

• US 10,496,636 B1
• Filed: 05/21/2019
• Issued: 12/03/2019
• Est. Priority Date: 05/24/2018
• Status: Active Grant

• Current Assignee: People.ai, Inc.
• Original Assignee: People.ai, Inc.
• Inventors: Rogynskyy, Oleg, Hermanek, Stefan, Halladay, Dylan, Korkuna, Ostap, Navarro, Jose Alberto Muniz
• Primary Examiner(s): Corrielus, Jean M
• Application Number:
  US16/418,769
• Publication Number:
  US 20190361878A1
• Time in Patent Office: 196 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
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• 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 assigning labels based on matching electronic activities to record objects. Electronic activities of one or more data source providers may be accessed. Each electronic activity may be matched with a record object of a system of record of the one or more data source providers. Record objects matching electronic activities may be identified. Values from object field-value pairs of the matching record objects may be extracted. Labels may be selected based on the extracted values. Associations between electronic activities and the selected labels may be stored.

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 one or more data source providers;

identifying, by the one or more processors, a record object matched with or with which to match a first electronic activity of the plurality of electronic activities;

determining, by the one or more processors, a record object type of the record object that corresponds to a first record object type or a second record object type, the first record object type corresponding to a process and including a stage field including a stage value indicating a proximity to a completion of the process and the second record object type corresponding to a participant of the first electronic activity;

responsive to determining that the record object type is the first record object type,

extracting, by the one or more processors, the stage value corresponding to the stage field of the record object;

selecting, by the one or more processors, a first label based on the extracted stage value and a labeling policy, the labeling policy including a first set of one or more rules or models to associate labels based on stage values of record objects corresponding to the first record object type; and

storing, by the one or more processors, in one or more data structures, an association between the first electronic activity and the selected first label corresponding to the stage value of the record object; and

responsive to determining that the record object type is the second record object type,

determining, by the one or more processors, by parsing the first electronic activity or by identifying at least one value corresponding to a title field or department field of the record object, a first value corresponding to a title of the participant or a department of the participant;

selecting, by the one or more processors, a second label based on the determined first value corresponding to the title of the participant or the department of the participant and the labeling policy, the labeling policy including a second set of one or more rules or models to associate labels based on titles or departments of participants of electronic activities corresponding to record objects of the second record object type; and

storing, by the one or more processors, in the one or more data structures, an association between the first electronic activity and the selected second label corresponding to the first value corresponding to the title of the participant or the department of the participant.

2. The method of claim 1, wherein storing the association between the first electronic activity and the selected first label comprises storing, by the one or more processors, in the one or more data structures, an association between the record object, the first electronic activity and the selected first label;

or

wherein storing the association between the first electronic activity and the selected second label comprises storing, by the one or more processors, in the one or more data structures, an association between the record object, the first electronic activity and the selected second label.

3. The method of claim 1, further comprising:

determining, by the one or more processors, a change to the stage value of the record object;

selecting, by the one or more processors, using the labeling policy, a third label responsive to determining the change in the value of the stage field of the record object; and

storing, by the one or more processors, in the one or more data structures, an association between the electronic activity and the third label.

4. The method of claim 1, further comprising:

determining, by the one or more processors, a second stage value corresponding to the stage field of the record object;

selecting, by the one or more processors, using the labeling policy, a third label responsive to determining the second stage value; and

storing, by the one or more processors, in the one or more data structures, an association between the electronic activity, the first label and the third label.

5. The method of claim 1, further comprising:

selecting, by the one or more processors, the selected first label based on at least one of a time of completion of the process or a likelihood of completion of the process.

6. The method of claim 5, further comprising:

determining, by the one or more processors, a change of the at least one of the time of completion or the likelihood of completion based on the first electronic activity; and

generating, by the one or more processors, the selected first label based on the change.

7. The method of claim 1, further comprising:

determining, by the one or more processors, a change in the stage value of the stage field of the record object; and

generating, by the one or more processors, the selected label based on the change in the stage value of the stage field.

8. The method of claim 1, further comprising:

determining, by the one or more processors, responsive to identifying the record object with which to match the electronic activity, context relating to the electronic activity, the context determined from one or more second electronic activities matched to the record object; and

generating by the one or more processors, a tag based on the context.

9. A system comprising:

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

access data from a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers;

identify a record object matched with or with which to match a first electronic activity of the plurality of electronic activities;

determine a record object type of the record object that corresponds to a first record object type or a second record object type, the first record object type corresponding to a process and including a stage field including a stage value indicating a proximity to a completion of the process and the second record object type corresponding to a participant of the first electronic activity;

responsive to determining that the record object type is the first record object type,

extract the stage value corresponding to the stage field of the record object;

select a first label based on the extracted stage value and a labeling policy, the labeling policy including a first set of one or more rules or models to associate labels based on stage values of record objects corresponding to the first record object type; and

store, in one or more data structures, an association between the first electronic activity and the selected first label corresponding to the stage value of the record object; and

responsive to determining that the record object type is the second record object type,

determine, by parsing the first electronic activity or by identifying at least one value corresponding to a title field or department field of the record object, a first value corresponding to a title of the participant or a department of the participant;

select a second label based on the determined first value corresponding to the title of the participant or the department of the participant and the labeling policy, the labeling policy including a second set of one or more rules or models to associate labels based on titles or departments of participants of electronic activities corresponding to record objects of the second record object type; and

store, in the one or more data structures, an association between the first electronic activity and the selected second label corresponding to the first value corresponding to the title of the participant or the department of the participant.

10. The system of claim 9, wherein the one or more processors store, in the one or more data structures, an association between the record object, the first electronic activity and the selected first label;

or wherein the one or more processors store, in the one or more data structures, an association between the record object, the first electronic activity and the selected second label.

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

determine a change to the stage value of the record object;

select using the labeling policy, a third label responsive to determining the change in the value of the stage field of the record object; and

store in the one or more data structures, an association between the electronic activity and the third label.

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

determine a second stage value corresponding to the stage field of the record object;

select, using the labeling policy, a third label responsive to determining the second stage value; and

store, in the one or more data structures, an association between the electronic activity, the first label and the third label.

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

select the selected first label based on at least one of a time of completion of the process or a likelihood of completion of the process.

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

determine a change of the at least one of the time of completion or the likelihood of completion based on the first electronic activity; and

generate the selected first label based on the change.

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

determine a change in the stage value of the stage field of the record object; and

generate the selected label based on the change in the stage value of the stage field.

16. 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:

accessing data from a plurality of electronic activities transmitted or received via electronic accounts associated with one or more data source providers;

identifying a record object matched with or with which to match a first electronic activity of the plurality of electronic activities;

determining a record object type of the record object that corresponds to a first record object type or a second record object type, the first record object type corresponding to a process and including a stage field including a stage value indicating a proximity to a completion of the process and the second record object type corresponding to a participant of the first electronic activity;

responsive to determining that the record object type is the first record object type,

extracting the stage value corresponding to the stage field of the record object;

selecting a first label based on the extracted stage value and a labeling policy, the labeling policy including a first set of one or more rules or models to associate labels based on stage values of record objects corresponding to the first record object type; and

storing, in one or more data structures, an association between the first electronic activity and the selected first label corresponding to the stage value of the record object; and

responsive to determining that the record object type is the second record object type,

determining, by parsing the first electronic activity or by identifying at least one value corresponding to a title field or department field of the record object, a first value corresponding to a title of the participant or a department of the participant;

selecting a second label based on the determined first value corresponding to the title of the participant or the department of the participant and the labeling policy, the labeling policy including a second set of one or more rules or models to associate labels based on titles or departments of participants of electronic activities corresponding to record objects of the second record object type; and

storing, in the one or more data structures, an association between the first electronic activity and the selected second label corresponding to the first value corresponding to the title of the participant or the department of the participant.