# US20150074033A1: Crowdsourced Electronic Documents Review And Scoring

- Kind: Published application
- Family: Distributed Electronic Document Review In A Blockchain System And Computerized Scoring Based On Textual And Visual Feedback (https://www.intellectualfrontiers.com/patents/distributed-electronic-document-review-in-a-blockchain-system-and-computerized-scoring-bas)
- USPTO status: Abandoned  --  Failure to Respond to an Office Action (as of 2017-01-23; record read 2026-09-27)
- Application: 14025472
- Filed: 2013-09-12
- Published: 2015-03-12
- Inventor: Shahid N. Shah
- Rights holder: Intellectual Frontiers LLC
- Classifications (CPC): G06N 5/02
- Continued in part by US9870591B2

## Licence or acquisition

Available for an exclusive or non-exclusive licence, field-of-use licences included, or for acquisition. Terms on inquiry. Write to hello+ip@intellectualfrontiers.com.

## Abstract

A system and a method for facilitating an expertise driven review and scoring of electronic documents in a crowdsourced environment. The system includes a server computer, a memory circuit and a processing circuit. The processing circuit is coupled to the memory circuit and includes or is coupled to a credentialing engine. The system further includes an expert scoring module. The system further includes a document reviewing and scoring engine coupled to the processing circuit. The document review and scoring module associates an aggregate score to the electronic document based on aggregation of the review ratings by crowdsourced experts and aggregate scores of each of the crowdsourced experts based on the set of attributes including one or more of the credentialed expertise, reputation of the expert, and the officiality.

## Independent claims

1. An ecosystem for an expertise driven review and scoring of electronic documents in a crowdsourced environment, said system comprising: a server computer; a memory circuit to store a plurality of common profiles associated with a plurality of crowdsourced experts, and further to store a plurality of federated profiles associated with each of said common profiles, wherein the federated and common profiles are created based on a plurality of federated sources distributed across a crowdsourced network; a processing circuit coupled to said memory circuit and including or coupled to: a credentialing engine to: allow a plurality of crowdsourced respondents to respond to said federated profiles associated with each of said plurality of experts and credential said plurality of experts, wherein said credentialing of each of said federated profiles associated with an expert of said plurality of experts contribute to credentialing of an entire common profile of said expert upon collation of said credentialed federated profiles, and wherein said federated profiles associated with said experts are credentialed from a plurality of respondents, wherein a crowdsourcing index is associated with said credentialing indicative of a degree of crowdsourcing such that said degree of crowdsourcing non-linearly affects said degree of credentialing that is indicative through said crowdsourcing index; an expert scoring module to: determine a set of attributes for said experts, said set of attributes including one or more of said crowdsourced credentialed expertise determined based on said credentialing of said federated and common profiles of said experts by said respondents, reputation of said expert indicative of a trust of a relevant community on said expert, and officiality indicative of a position or a designation of said expert in a relevant job, wherein each of said attributes are assigned varying weights; and determine an aggregate score of an expert based on said one or more attributes in association with said assigned weights; a document reviewing and scoring engine coupled to said processing circuit to: receive review comments along with a document rating by each of said crowdsourced experts for an electronic document, wherein a facility to review and score said electronic document is provided to said experts with a defined threshold of said aggregate score as a minimum criteria; and associate an aggregate score to said electronic document based on aggregation of said review ratings by said crowdsourced experts and said aggregate scores of each of said crowdsourced experts based on said set of attributes including one or more of said credentialed expertise, reputation of said expert, and said officiality.

14. A method for performing an expertise driven review and scoring of electronic documents in a crowdsourced environment, said method comprising: receiving a document for reviewing and scoring by a plurality of crowdsourced experts; determining a set of expert attributes including one or more of crowdsourced credentialing, officiality, and reputation, wherein said reputation is indicative of a trust of a relevant community on said expert, and said officiality is indicative of a position or a designation of said expert in a relevant job and said credentialed expertise is indicative of degree of credentialing of an expert federated and common profiles by crowdsourced respondents; determining an aggregate score of an expert based on said one or more attributes; receiving review comments along with a document rating by each of said crowdsourced experts; and associating an aggregate score to said electronic document based on an aggregation of said review ratings by said crowdsourced experts and said aggregate scores of each of said crowdsourced experts based on said set of attributes including one or more of said credentialed expertise, reputation of said expert, and said officiality.

18. A non-transitory program storage device readable by computer, and comprising a program of instructions executable by said computer to perform a method for performing an expertise driven review and scoring of electronic documents in a crowdsourced environment, said method comprising: receiving a document for reviewing and scoring by a plurality of crowdsourced experts; determining a set of expert attributes including one or more of crowdsourced credentialing, officiality, and reputation, wherein said reputation is indicative of a trust of a relevant community on said expert, and said officiality is indicative of a position or a designation of said expert in a relevant job and said credentialed expertise is indicative of degree of credentialing of an expert federated and common profiles by crowdsourced respondents; determining an aggregate score of an expert based on said one or more attributes; receiving review comments along with a document rating by each of said crowdsourced experts, and associating an aggregate score to said electronic document based on an aggregation of said review ratings by said crowdsourced experts and said aggregate scores of each of said crowdsourced experts based on said set of attributes including one or more of said credentialed expertise, reputation of said expert, and said officiality.

Source: https://www.intellectualfrontiers.com/patents/distributed-electronic-document-review-in-a-blockchain-system-and-computerized-scoring-bas/us20150074033a1