ASSESSMENT METHOD, REWARD SETTING METHOD, COMPUTER, AND PROGRAM

• US 20200134653A1
• Filed: 10/02/2019
• Published: 04/30/2020
• Est. Priority Date: 10/29/2018
• Status: Active Application

• Current Assignee: Fronteo, Inc.
• Original Assignee: Fronteo, Inc.
• Inventors: NISHINO, Sayaka, TAMURA, Ryota, IGUCHI, Shinya
• Application Number:
  US16/590,670
• Publication Number:
  US 20200134653A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0217 involving input on products or services in exchange for incentives or rewards
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26

Abstract

An assessment method which is capable of appropriately assessing review ability of a reviewer and a reward setting method which is capable of appropriately setting a reward to be paid to the reviewer are realized. A computer includes a memory and a controller, and the controller executes efficiency evaluation processing of evaluating review efficiency of a reviewer to be assessed in accordance with a predicted review period of each piece of electronic data and an actual review period, accuracy evaluation processing of evaluating review accuracy of the reviewer to be assessed by examining a review result by the reviewer to be assessed, and assessment processing of assessing review ability of the reviewer to be assessed in accordance with the review efficiency evaluated in the efficiency evaluation processing and the review accuracy evaluated in the accuracy evaluation processing.

Claims

1. An assessment method for assessing review ability of a reviewer to be assessed who reviews a data set using a computer including a controller and a memory which stores the data set including at least one piece of electronic data, the assessment method comprising:

efficiency evaluation processing executed by the controller evaluating review efficiency of the reviewer to be assessed in accordance with a predicted review period of each piece of electronic data and an actual review period actually taken for the reviewer to be assessed to do review work on the electronic data;

accuracy evaluation processing executed by the controller evaluating review accuracy of the reviewer to be assessed by examining a review result obtained by the reviewer to be assessed reviewing the data set; and

assessment processing executed by the controller assessing the review ability of the reviewer to be assessed in accordance with the review efficiency evaluated in the efficiency evaluation processing and the review accuracy evaluated in the accuracy evaluation processing.

2. The assessment method according to claim 1, further comprising:

prediction processing executed by the controller calculating the predicted review period in accordance with a prediction model constructed in advance using a reviewed data set; and

measurement processing executed by the controller measuring the actual review period,

wherein the efficiency evaluation processing is processing of evaluating the review efficiency of the reviewer to be assessed from the actual review period obtained in the measurement processing on a basis of the predicted review period obtained in the prediction processing.

3. The assessment method according to claim 1,

wherein the prediction model is a prediction model in which a feature amount of content of each piece of electronic data is input and a predicted review period of the electronic data is output, and is a prediction model constructed through machine learning which uses the reviewed data set as learning data.

4. The assessment method according to claim 1,

wherein the review work is work of judging whether or not electronic data satisfies extraction conditions determined in advance, and

the accuracy evaluation processing is processing of evaluating the review accuracy of the reviewer to be assessed by comparing a judgment result in the review work by the reviewer to be assessed with a judgment result in the review work by a reviewer other than the reviewer to be assessed.

5. The assessment method according to claim 1,

wherein the assessment processing is processing of assessing the review ability of the reviewer to be assessed using an algorithm determined in advance in which the review efficiency and the review accuracy of the reviewer to be assessed are input and the review ability of the reviewer to be assessed is output.

6. The assessment method according to claim 1, further comprising:

efficiency output processing executed by the controller visualizing the review efficiency and outputting the visualized review efficiency.

7. The assessment method according to claim 1, further comprising:

ability output processing executed by the controller visualizing the review ability and outputting the visualized review ability.

8. A reward setting method for setting a reward to be paid to a reviewer in accordance with ability of the reviewer assessed using the assessment method according to claim 1, the reward setting method comprising:

calculation processing of calculating the reward so that, when review ability of a first reviewer assessed using the assessment method is higher than review ability of a second reviewer assessed using the assessment method, a reward to be paid to the first reviewer becomes more than a reward to be paid to the second reviewer.

9. The reward setting method according to claim 8,

wherein the calculation processing is processing of calculating the reward so as not to fall below a lower limit value of the reward determined in advance and so as not to exceed an upper limit value of the reward determined in advance.

10. A computer including a memory which stores a data set including at least one piece of electronic data, and a controller, and assessing review ability of a reviewer to be assessed who reviews the data set,

the controller executing:

efficiency evaluation processing of evaluating review efficiency of the reviewer to be assessed in accordance with a predicted review period of each piece of electronic data and an actual review period actually taken for the reviewer to be assessed to do review work on the electronic data;

accuracy evaluation processing of evaluating review accuracy of the reviewer to be assessed by examining a review result obtained by the reviewer to be assessed reviewing the data set; and

assessment processing of assessing the review ability of the reviewer to be assessed in accordance with the review efficiency evaluated in the efficiency evaluation processing and the review accuracy evaluated in the accuracy evaluation processing.