Systems and methods for determining a completion score of a record object from electronic activities

• US 10,496,634 B1
• Filed: 04/29/2019
• 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, Markovsky, Yury, Jeske, Eric, Lutsaievska, Tetiana, Li, Hang
• Primary Examiner(s): Ortiz Ditren, Belix M
• Application Number:
  US16/398,260
• Publication Number:
  US 20190361866A1
• Time in Patent Office: 218 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 determining a completion score for a record object based on electronic activities. The method includes accessing record objects, each of which corresponds to a record object type and includes object fields having object field-values. The method includes selecting one of the record objects. The method includes identifying electronic activities transmitted or received associated with the record object. Each of the electronic activities has a timestamp indicating a receipt time or transmission time of the respective electronic activity. The method includes determining a participant of each of the electronic activities. The method includes determining a completion score indicating a likelihood of completing an event associated with the record object based on the timestamp of each of the electronic activities and the participant of each of the electronic activities. The method includes storing an association between the record object and the completion score.

Claims

1. A method comprising:

accessing, by one or more processors, data from a plurality of record objects of one or more systems of record, each record object of the plurality of record objects corresponding to a record object type and comprising one or more object fields having one or more object field-values;

selecting, by the one or more processors, a first record object of the plurality of record objects;

identifying, by the one or more processors, a plurality of electronic activities transmitted or received via electronic accounts and associated with the first record object, each of the plurality of electronic activities having a timestamp indicating a receipt time or transmission time of the respective electronic activity;

determining, by the one or more processors and responsive to parsing data from the plurality of electronic activities, at least one participant of each of the plurality of electronic activities;

determining, by the one or more processors, for the at least one participant of each of the plurality of electronic activities, at least one of a role, a title, or a department corresponding to the at least one participant;

determining, by the one or more processors, a completion score indicating a likelihood of completing an event associated with the first record object, the completion score based on the timestamp of each of the plurality of electronic activities and at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities; and

storing, by the one or more processors, in one or more data structures, an association between the first record object and the completion score.

2. The method of claim 1, further comprising:

determining, by the one or more processors, a time distribution of the plurality of electronic activities based on the timestamp for each of the plurality of electronic activities; and

wherein determining, by the one or more processors, the completion score comprises determining the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the time distribution.

3. The method of claim 1, further comprising:

maintaining, by the one or more processors, a plurality of node profiles corresponding to a plurality of unique entities, each node profile of the plurality of node profiles including at least one value corresponding to a role field, a title field, or a department field;

identifying, by the one or more processors, a node profile from the plurality of node profiles for the at least one participant of each of the plurality of electronic activities;

determining, by the one or more processors and for the at least one participant of each of the plurality of electronic activities, from the at least one of the role field, the title field, or the department field, at least one of the role, the title, or the department corresponding to the participant;

and wherein determining, by the one or more processors, the completion score comprises determining the completion score based on the timestamp of each of the plurality of electronic activities and the role corresponding to the at least one participant.

4. The method of claim 1, wherein identifying, by the one or more processors, the plurality of electronic activities further comprises selecting the plurality of electronic activities responsive to the timestamp of each of the plurality of electronic activities being within a time window from a current time.

5. The method of claim 1, further comprising:

identifying, by the one or more processors, a size value of an object field-value pair of the one or more object field-values for the first record object;

and wherein determining, by the one or more processors, the completion score further comprises determining the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the size value.

6. The method of claim 1, further comprising:

identifying, by the one or more processors, a subset of the plurality of record objects responsive to each of the subset of the plurality of record objects having a similarity score to the first record object that satisfies a threshold;

determining, by the one or more processors, a status score for each of the subset of the plurality of record objects;

and wherein determining, by the one or more processors, the completion score further comprises determining the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the status score for each of the subset of the plurality of record objects.

7. The method of claim 1, wherein the timestamp of each of the plurality of electronic activities is a first timestamp and further comprising:

determining, by the one or more processors, a second timestamp associated with a first occurrence of the at least one participant of each of the plurality of electronic activities;

and wherein determining, by the one or more processors, the completion score further comprises determining the completion score based on the first timestamp, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the second timestamp associated with the first occurrence of the at least one participant of each of the plurality of electronic activities.

8. The method of claim 1, further comprising:

identifying, by the one or more processors, a stage value of an object field-value of the first record object, the stage value indicating a proximity to a completion on an event associated with the first record object;

determining, by the one or more processors, a duration since an update to the stage value;

and wherein determining, by the one or more processors, the completion score further comprises determining the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and duration since the update to the stage value.

9. The method of claim 1, further comprising:

identifying, by the one or more processors, a second plurality of record objects having a second record object type and associated with the first record object;

identifying, by the one or more processors, a first set of node profiles maintained by the one or more processors, each of the first set of node profiles associated with one of the second plurality of record objects;

identifying, by the one or more processors, a second set of node profiles maintained by the one or more processors, each of the second set of node profiles associated with the at least one participant of each of the plurality of electronic activities;

and wherein determining, by the one or more processors, the completion score further comprises determining the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and a comparison of the first set of node profiles and the second set of node profiles.

10. A system, comprising:

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

access data from a plurality of record objects of one or more systems of record, each record object of the plurality of record objects corresponding to a record object type and comprising one or more object fields having one or more object field-values;

select a first record object of the plurality of record objects;

identify a plurality of electronic activities transmitted or received via electronic accounts and associated with the first record object, each of the plurality of electronic activities having a timestamp indicating a receipt time or transmission time of the respective electronic activity;

determine, responsive to parsing data from the plurality of electronic activities, at least one participant of each of the plurality of electronic activities;

determine, for the at least one participant of each of the plurality of electronic activities, at least one of a role, a title, or a department corresponding to the at least one participant;

determine a completion score indicating a likelihood of completing an event associated with the first record object, the completion score based on the timestamp of each of the plurality of electronic activities and at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities; and

store in one or more data structures, an association between the first record object and the completion score.

11. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

determine, by the one or more processors, a time distribution of the plurality of electronic activities based on the timestamp for each of the plurality of electronic activities; and

wherein to determine the completion score, the one or more hardware processors are configured to determine, by the one or more processors, the completion score based on at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the time distribution.

12. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

maintain, by one or more processors, a plurality of node profiles corresponding to a plurality of unique entities, each node profile of the plurality of node profiles including at least one value corresponding to a role field, a title field, or a department field;

identify, by the one or more processors, a node profile from the plurality of node profiles for the at least one participant of each of the plurality of electronic activities;

determine, by the one or more processors and for the at least one participant of each of the plurality of electronic activities, from the at least one of the role field, the title field, or the department field, at least one of the role, the title, or the department corresponding to the participant; and

wherein to determine the completion score, the one or more hardware processors are configured to determine, by the one or more processors, the completion score based on the timestamp of each of the plurality of electronic activities and the role corresponding to the at least one participant.

13. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

select the plurality of electronic activities responsive to the timestamp of each of the plurality of electronic activities being within a time window from a current time.

14. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

identify a size value of an object field-value pair of the one or more object field-values for the first record object; and

wherein to determine the completion score, the one or more hardware processors are configured to determine the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title or the department of the at least one participant of each of the plurality of electronic activities and the size value.

15. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

identify a subset of the plurality of record objects responsive to each of the subset of the plurality of record objects having a similarity score to the first record object that satisfies a threshold;

determine a status score for each of the subset of the plurality of record objects; and

wherein to determine the completion score, the one or more hardware processors are configured to determine the completion score based on the timestamp of each of the plurality of electronic activities, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the status score for each of the subset of the plurality of record objects.

16. The system of claim 10, wherein the timestamp of each of the plurality of electronic activities is a first timestamp and wherein the one or more hardware processors are further configured by machine-readable instructions to:

determine a second timestamp associated with a first occurrence of the at least one participant of each of the plurality of electronic activities; and

wherein to determine the completion score, the one or more hardware processors are configured to determine the completion score based on the timestamp associated with the first occurrence of the at least one participant of each of the plurality of electronic activities.

17. The system of claim 10, wherein the one or more hardware processors are further configured by machine-readable instructions to:

identify a stage value of an object field-value of the first record object, the stage value indicating a proximity to a completion on an event associated with the first record object;

determine a duration since an update to the stage value;

and wherein to determine the completion score, the one or more hardware processors are configured to determine the completion score based on the first timestamp, at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities and the second timestamp associated with a first occurrence of the at least one participant of each of the plurality of electronic activities.

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

access data from a plurality of record objects of one or more systems of record, each record object of the plurality of record objects corresponding to a record object type and comprising one or more object fields having one or more object field-values;

select a first record object of the plurality of record objects;

identify a plurality of electronic activities transmitted or received via electronic accounts and associated with the first record object, each of the plurality of electronic activities having a timestamp indicating a receipt time or transmission time of the respective electronic activity;

determine responsive to parsing data from the plurality of electronic activities, at least one participant of each of the plurality of electronic activities;

determine, for the at least one participant of each of the plurality of electronic activities, at least one of a role, a title, or a department corresponding to the at least one participant;

determine a completion score indicating a likelihood of completing an event associated with the first record object, the completion score based on the timestamp of each of the plurality of electronic activities and at least one of the role, the title, or the department of the at least one participant of each of the plurality of electronic activities; and

store in one or more data structures, an association between the first record object and the completion score.