IP Library › Granted Patent US 11,010,725
Granted Patent B2
US 11,010,725 · App. 15/805,211 · Granted May 18, 2021

Determining validity of service recommendations

Inventors: Schayne Bellrose (Poughkeepsie, NY); Pasquale A. Catalano (Wallkill, NY); Jerry Chuaypradit (Monroe, NY); Andrew Crimmins (Montrose, NY); Preston Lane (Poughkeepsie, NY); Juan Merchan (Poughkeepsie, NY); Rorie Paul Reyes (Kingston, NY)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06Q10/20G06Q10/0639G06Q30/018
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Quick Facts
Patent No.
US 11,010,725
App. No.
15/805,211
Granted
May 18, 2021
Kind
B2
Abstract

Embodiments include techniques for determining the validity of service recommendations, where the techniques include receiving a service provider recommendation for a device from a service provider, and receiving device inputs and service provider inputs associated with the device. The techniques also include performing an input analysis on the device inputs to determine a predicted recommendation, and determining a trust level score for the service provider based at least in part on the service provider inputs, and comparing the service provider recommendation and the predicted recommendation. Techniques include performing, based at least in part on the trust level score, a value analysis and a severity analysis, and generating a recommended action based at least in part on the value analysis and the severity analysis.

Claims (26)

1. A computer-implemented method for determining validity of service recommendations, the computer-implemented method comprising:

receiving, via a processor, a service provider recommendation for a device from a service provider;

receiving device inputs and service provider inputs associated with the device;

determining a predicted recommendation based on the device inputs;

determining a trust level score for the service provider based at least in part on the service provider inputs, and comparing the service provider recommendation from the service provider and the predicted recommendation;

performing, based at least in part on the trust level score, a value analysis and a severity analysis, wherein the value analysis further comprises:

receiving a service provider cost for a service;

receiving, from a user, cost information for the service and a trust value; and

determining a vCOST value for the service of the service provider recommendation, wherein the vCOST value is a value calculated according to the following equation:

v COST=COST−(COST*TRUST)

wherein COST is the service provider cost for the service, and TRUST is a trust value;

responsive to determining the vCOST value for the service provider recommendation, determining a vCOST value for at least one secondary service provider and a vCOST value for a self-service option, wherein the vCOST value for the at least one secondary service provider is a value calculated using a cost for the service for the at least one secondary service provider and the trust value, wherein the vCOST value for the self-service option is a value calculated using a cost for the self-service option and the trust value;

comparing the vCOST value for the service provider to the vCOST value for the at least one secondary service provider and vCOST value for the self-service option; and

selecting a lowest vCOST value based at least in part on the comparison;

generating a recommended action based at least in part on the value analysis and the severity analysis;

providing an indication, wherein the indication includes the generated recommended action and a recommendation to perform the generated recommended action based at least in part on the value analysis and the severity analysis, wherein the recommendation to perform the generated recommended action includes a result of the value analysis and a result of the severity analysis, otherwise provide an indication to not perform the generated recommended action based at least in part on the value analysis and the severity analysis, wherein the indication to not perform the generated recommended action includes the result of the value analysis and the result of the severity analysis; and

performing the recommended action.

2. The computer-implemented method of claim 1 , wherein the service provider recommendation is received by speech-to-text function.

3. The computer-implemented method of claim 1 , wherein the device inputs include at least one of a device service history, device model issues, diagnostic data, or device profile information.

4. The computer-implemented method of claim 1 , wherein the service provider inputs include at least one of a service provider profile and a competitor service provider profile.

5. The computer-implemented method of claim 1 , wherein determining the trust level score is based at least in part on the service provider inputs and analyzing reviews including at least one of service provider reviews or social media reviews that are associated with the service provider.

6. The computer-implemented method of claim 1 , further comprising:

setting a reminder for the recommended action based on the value analysis and the severity analysis.

7. The computer-implemented method of claim 1 , wherein the severity analysis includes searching, based on the trust level score, a table for a severity rating for the service; and

determining the severity rating.

8. The computer-implemented method of claim 1 , wherein the severity analysis and the value analysis are performed simultaneously.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 7, 2017
From: BELLROSE, SCHAYNE; CATALANO, PASQUALE A.; CHUAYPRADIT, JERRY; CRIMMINS, ANDREW; LANE, PRESTON; MERCHAN, JUAN; REYES, RORIE PAUL
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 044048/0980 →
Continuity (2)
Continuation 15716767 · Sep 27, 2017
Related Publication 20190095874A1 · Mar 28, 2019