Patent Issued for User generated tag collection system and method (USPTO 11675750): Hartford Fire Insurance Company

2023 JUL 05 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Cultrera, Steven J (Newington, CT, US), Drennan, III, Arthur Paul (West Granby, CT, US), Kazmi, Saira A. (Glastonbury, CT, US), Plock, Justin G. (Southport, CT, US), Srinivasaraghavan, Vasanth Madhavan (Manchester, CT, US), filed on March 4, 2020, was published online on June 13, 2023.

The patent’s assignee for patent number 11675750 is Hartford Fire Insurance Company (Hartford, Connecticut, United States).

News editors obtained the following quote from the background information supplied by the inventors: “An entity, such as an enterprise that analyzes risk information, may want to analyze large amounts of data, such as image data. For example, a risk enterprise might want to analyze tens of thousands of image files to look for patterns (e.g., a particular type of damage has occurred more frequently under particular circumstance). Note that an entity might analyze this data in connection with different types of risk-related applications, and, moreover, different applications may need to analyze the data differently. For example, a picture of a business or residence might have different meanings depending on the types of risk being evaluated. It can be difficult to identify patterns across such large amounts of data and different types of applications. In addition, manually managing the different needs and requirements (e.g., different business logic rules) associated with different applications can be a time consuming and error prone process.

“Artificial Intelligence (“AI”) can accelerate the rate at which an enterprise can analyze data. AI capabilities, however, rely upon the manual curation of a “golden” or “ground truth” datasets (that typically involves a significant amount of time) and the strength of the AI is directly correlated to the accuracy and quality of the golden dataset. Note that creating a high-quality dataset to train machine learning and similar AI models can be a costly and time-consuming project.

“As a result, it would be desirable to provide systems and methods to efficiently and accurately tag documents (including traditional document files, images, structured and unstructured text, audio and video files) in connection with risk-related and other applications.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “According to some embodiments, systems, methods, apparatus, computer program code and means are provided for efficiently and accurately tagging document data. In some embodiments, an input document is received at a tagging platform, via a communication device, and associates it with a tag request. The tagging platform automatically selects at least one electronic record associated with a first user from a user data store containing electronic records associated with users (each record including at least a user identifier and a user communication address). The input document and tag request are transmitted to the communication address associated with the first user, and a document tag is received from the first user. The tagging platform may then store the document tag in a document mining result database by adding an entry to the database identifying the received document tag and transmit an indication associated with the document mining result database to a plurality of risk applications.

“Some embodiments provide: means for receiving an input document at a tagging platform via a communication device; means for associating the input document with a tag request; means for automatically selecting at least one electronic record associated with a first user from a user data store containing electronic records associated with users, each electronic record including at least a user identifier and a user communication address; means for transmitting the input document and tag request to the communication address associated with the first user; means for receiving a document tag from the first user; means for storing the document tag in a document mining result database by adding an entry to the database identifying the received document tag; and means for transmitting an indication associated with the document mining result database to a plurality of risk applications

“A technical effect of some embodiments of the invention is an improved and computerized way of tagging document information to provide improved results for risk-related and other applications. With these and other advantages and features that will become hereinafter apparent, a more complete understanding of the nature of the invention can be obtained by referring to the following detailed description and to the drawings appended hereto.”

The claims supplied by the inventors are:

“1. A document tagging system, comprising: a communication device to receive an input document; a user data store containing electronic records associated with users, each electronic record including at least a user identifier and a user communication address; and a tagging platform, coupled to the communication device and the user data store, including: a computer processor; and a computer storage device in communication with said computer processor and storing instructions adapted to be executed by said computer processor to: receive the input document, associate the input document with a tag request, automatically select at least one electronic record associated with a first user, transmit the input document and tag request to the communication address associated with the first user, receive a document tag from the first user, wherein the document tag is any object describing a document, store the document tag in a document mining result database by adding an entry to the document mining result database identifying the received document tag, and transmit an indication associated with the document mining result database to a plurality of risk applications associated with phases of an insurance process, the phases comprising at least a prospecting flow, a quoting flow, a pricing flow, a book management flow, and a policy renewal flow, wherein the risk applications are associated with an enterprise, the users comprise employees of the enterprise, and access to a computer system by the first user is dependent on and provided after receipt of the document tag from the user.

“2. The system of claim 1, wherein the tagging platform sends the input document to multiple users and aggregates multiple document tags from those users.

“3. The system of claim 1, wherein receipt of the document tag results in an automatic generation of a subsequent tag request in accordance with a tag hierarchy.

“4. The system of claim 1, wherein the electronic record includes a user quality attribute indicative of a predicted document tag accuracy.

“5. The system of claim 1, wherein the document mining result database further store at least one of: (i) an amount of time associated with the document tag, (ii) a time of day associated with the document tag, (iii) a day of week associated with the document tag, and (iv) a time of year associated with the document tag.

“6. The system of claim 1, wherein execution of the stored instructions further causes the computer processor to: receive, from at least one of the risk applications, feedback information associated with the document tag, and based on the received feedback information, automatically update information in the user data store.

“7. The system of claim 1, wherein the input document is associated with at least one of: (i) a risk claim file, (ii) a risk claim note, (iii) a medical report, (iv) a police report, (v) social network data, (vi) web image data, (vii) Internet of Things data, (viii) Global Positioning System (“GPS”) satellite data, (ix) activity tracking data, (x) big data information, (xi) a loss, (xii) an injury, (xiii) an image associated with a final notice of loss statement, (xiv) video chat stream, (xv) optical character recognition data, (xvi) third-party data, and (xvii) a governmental agency.

“8. The system of claim 1, wherein the transmitted indication is to: (i) trigger a risk application, or (ii) update a risk application.

“9. The system of claim 1, wherein the transmitted indication is associated with a variable or weighing factor of a predictive model.

“10. The system of claim 1, wherein the input document comprises at least one of: (i) an image, (ii) a word processing document, (iii) a video, and (iv) an audio file.

“11. The system of claim 1, wherein the tag is associated with at least one of: (i) an item present within an image, and (ii) an activity associated with an image.

“12. The system of claim 1, wherein the entry added to the document mining result database includes at least one of: (i) an image identifier, (ii) an insert date, (iii) an image source, (iv) a rule identifier, and (v) a line of business.

“13. The system of claim 1, wherein the computer storage device further stores instructions adapted to be executed by said computer processor to: identify at least a portion of the input document as being connected with one of training data and non-training data, and associate that portion of the input document with a custom tag based on one of the training data and non-training data.

“14. The system of claim 1, wherein said automatic selection is performed via cloud analytics associated with at least one of: (i) object storage, (ii) a data catalog, (iii) a data lake store, (iv) a data factory, (v) machine learning, and (vi) artificial intelligence services.

“15. A computer-implemented method, comprising: receiving an input document at a tagging platform via a communication device; associating the input document with a tag request; automatically selecting at least one electronic record associated with a first user from a user data store containing electronic records associated with users, each electronic record including at least a user identifier and a user communication address; transmitting the input document and tag request to the communication address associated with the first user; receiving a document tag from the first user wherein the document tag is any object describing a document; storing the document tag in a document mining result database by adding an entry to the document mining result database identifying the received document tag; and transmitting an indication associated with the document mining result database to a plurality of risk applications associated with phases of an insurance process, the phases comprising at least a prospecting flow, a quoting flow, a pricing flow, a book management flow, and a policy renewal flow, wherein the risk applications are associated with an enterprise, the users comprise employees of the enterprise, and access to a computer system by the first user is dependent on and provided after receipt of the document tag from the first user.

“16. The method of claim 15, wherein the tagging platform sends the input document to multiple users and aggregates multiple document tags from those users.

“17. The method of claim 15, wherein receipt of the document tag results in an automatic generation of a subsequent tag request in accordance with a tag hierarchy.

“18. A non-transitory computer-readable medium storing instructions adapted to be executed by a computer processor to perform a method, said method comprising: receiving an input document at a tagging platform via a communication device; associating the input document with a tag request; automatically selecting at least one electronic record associated with a first user from a user data store containing electronic records associated with users, each electronic record including at least a user identifier and a user communication address; transmitting the input document and tag request to the communication address associated with the first user; receiving a document tag from the first user, wherein the document tag is any object describing a document; storing the document tag in a document mining result database by adding an entry to the document mining result database identifying the received document tag; and transmitting an indication associated with the document mining result database to a plurality of risk applications associated with phases of an insurance process, the phases comprising at least a prospecting flow, a quoting flow, a pricing flow, a book management flow, and a policy renewal flow, wherein the risk applications are associated with an enterprise, the users comprise employees of the enterprise, and access to a computer system by the first user is dependent on and provided after receipt of the document tag from the user.

“19. The medium of claim 18, wherein the electronic record includes a user quality attribute indicative of a predicted document tag accuracy.”

For additional information on this patent, see: Cultrera, Steven J. User generated tag collection system and method. U.S. Patent Number 11675750, filed March 4, 2020, and published online on June 13, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11675750)&db=USPAT&type=ids

(Our reports deliver fact-based news of research and discoveries from around the world.)