Method for computing subjective dissimilarities among discrete entities

• US 20050222828A1
• Filed: 04/01/2005
• Published: 10/06/2005
• Est. Priority Date: 04/02/2004
• Status: Abandoned Application

• Current Assignee: Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Original Assignee: Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Inventors: Colonius, Hans, Dzhafarov, Ehtibar
• Application Number:
  US11/097,585
• Publication Number:
  US 20050222828A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures

Abstract

A method for computing subjective dissimilarities among discrete entities is provided. The method includes the steps of presenting a plurality of entities to a perceiver, determining discrimination probabilities among the entities, and computing Fechnerian distances and the shortest pathways between the entities.

Claims

1. A method of computing subjective dissimilarities among discrete entities, the method comprising the steps of:

presenting a plurality of discrete entities to a perceiver,

receiving from the perceiver an indication as to whether the entities are the same or different,

determining a discrimination probability for each pair of entities based on the indication received from the perceiver,

computing Fechnerian distances between the entities based on the discrimination probabilities,

computing geodesic loop for all pairs of entities, and

analyzing the Fechnerian distances to determine subjective dissimilarities among the entities.

2. The method of claim 1, wherein the perceiver is one of a person, and a biological organism.

3. The method of claim 1, wherein the perceiver is one of a device and a computational procedure.

4. The method of claim 1, wherein the presenting step includes transmitting a characteristic of the entities over a network.

5. The method of claim 1, wherein the computing step includes the steps of computing the overall distance between the entities in each pair of entities and the shortest pathways leading from one entity to another and back.

6. A method for computing subjective dissimilarities among discrete objects, the method comprising the steps of:

receiving discrimination data for a plurality of discrete objects,

computing a first matrix of discrimination probabilities for the selected objects,

checking the first matrix for one of regular minimality and regular maximality,

identifying a point of subjective equality for each row and column in the first matrix,

computing a second matrix of psychometric increments for each pair of objects,

computing the shortest pathways leading from one entity to another and back, and

identifying the distance between objects for each pair of objects as the length of the geodesic pathways.

7. The method of claim 6, further comprising the step of generating the discrimination data by querying at least one perceiver.

8. The method of claim 6, wherein the discrimination probabilities are probabilities that the objects are different.

9. The method of claim 6, further comprising the step of assigning a label to each object.

10. The method of claim 6, wherein the points of subjective equality are identified by comparing row objects and column objects of the first matrix and identical labels are assigned to objects which are each other'"'"'s points of subjective equality.

11. The method of claim 6, wherein the psychometric increments are computed according to the equation Φ

(S_i, S_j)=p_ij−

p_ii.

12. The method of claim 6, wherein the length of a chain x₁, x₂, . . . , x_k is computed according to the formula L(x₁, x₂, . . . , x_k)=Σ

<sup>k−

1</sup>_m=1 Φ

(x_m, x_m+1).

13. The method of claim 6, wherein the minimum distances are computed according to the equation L_min(S_i, S_j)=the smallest L(x₁, x₂, . . . , x_k) across all chains x₁, x₂, . . . , x_k with x₁=S_i and x_k=S_j.

14. The method of claim 6, further comprising the step of generating a geodesic loop for each pair of objects.

15. A system for computing subjective dissimilarities among discrete objects, the system comprising:

an input device,

a processor adapted to;

receive data representing discrimination probabilities for a plurality of objects, and

compute Fechnerian distances between the objects using the data representing discrimination probabilities, and

a display operatively coupled to the processor to graphically depict the Fechnerian distances between the objects.

16. The system of claim 15, further comprising a communication network, wherein the input device is operatively coupled to the processor via the communication network.

17. The system of claim 15, wherein the input device and the display are included in a remote device, and the remote device is operatively coupled to the processor by a communication network.

18. The system of claim 15, wherein the processor is further adapted to check for regular minimality of the discrimination data.

19. The system of claim 15, wherein the processor is further adapted to generate geodesic loops for each pair of objects.