Interface device, inferring system, and visual expression method

• US 20050202845A1
• Filed: 02/28/2005
• Published: 09/15/2005
• Est. Priority Date: 03/01/2004
• Status: Active Grant

• Current Assignee: DENSO Corporation
• Original Assignee: DENSO Corporation
• Inventors: Sasaki, Mikio
• Granted Patent: US 7,668,824 B2
• Time in Patent Office: Days
• US Class Current: 455/556.200
• CPC Class Codes: G08G 1/0962 having an indicator mounted inside the vehicle, e.g. giving voice messages
• CPC Class Codes: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: H04M 1/72451 according to schedules, e.g. using calendar applications
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• CPC Class Codes: H04M 1/72457 according to geographic location
• CPC Class Codes: Y10S 707/92 Navigation
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

When a start key is operated, an inferring process of estimating a demand of a user is executed on the basis of preset situation data, a user profile, and situation data manually input via a situation setting key. Based on the inference result, a genre list and a contents list are reconstructed so that genres and contents items are arranged in order of the degree of a demand of the user. The top three genres extracted from the reconstructed genre list are associated with three selection keys, and the names of the associated genres or labels of the genres are displayed in genre name display parts. It enables the user to easily and instantaneously select one of contents items to be processed.

Claims

1. An interface device having at least one unit to be operated, the device that is used to select one of a plurality of contents items to be processed, the device comprising:

demand estimating means of obtaining situation data for grasping a situation of a user and estimating a demand of the user based on the situation data;

group recommendation order setting means for setting a group recommendation order of a plurality of contents groups obtained by classifying the contents items in accordance with a demand estimated by the demand estimating means;

assigning means for associating a predetermined contents group with the unit to be operated in accordance with the group recommendation order set by the group recommendation order setting means, wherein the predetermined contents group is high in the group recommendation order set by the group recommendation order setting means; and

process object selecting means for selecting, as an object to be processed, one of contents items belonging to the predetermined contents group associated with the unit to be operated in response to an operation on the unit to be operated.

2. The interface device according to claim 1,

wherein the group recommendation order setting means sets a group recommendation order of the contents groups for each group family obtained by previously classifying the contents groups, and sets a group family recommendation order of the group families, and

wherein the assigning means selects a group family that is high in the group family recommendation order in accordance with the group family recommendation order set by the group recommendation order setting means and associates a highest contents group that is highest in the group recommendation order in the selected group family, with the unit to be operated.

3. The interface device according to claim 2, further comprising

group switching means for switching a contents group to be associated with the unit to be operated in accordance with the group family recommendation order which is set by the group recommendation order setting means.

4. The interface device according to claim 3,

wherein the group switching means switches a contents group in accordance with a pre-designated special operation to be performed on the unit to be operated or an operation to be performed on an auxiliary unit to be operated which is attached to the unit to be operated.

5. The interface device according to claim 2,

wherein at least part of the unit to be operated is fixedly associated with a pre-designated group family.

6. The interface device according to claim 1,

wherein at least part of the unit to be operated is fixedly associated with a pre-designated contents group.

7. The interface device according to claim 1, further comprising

contents recommendation order setting means for setting a contents recommendation order of each of contents items included in each of the contents groups in accordance with a demand estimated by the demand estimating means,

wherein the process object selecting means selects, as an object to be processed, one of the contents items that is highest in the contents recommendation order which is set by the contents recommendation order setting means.

8. The interface device according to claim 7, further comprising

contents switching means for switching one of the contents items to be selected by the process object selecting means in accordance with the contents recommendation order set by the contents recommendation order setting means.

9. The interface device according to claim 8,

wherein the contents switching means switches a contents item each time the same unit to be operated is operated.

10. The interface device according to claim 1, further comprising

input means used by the user to input the situation data,

wherein the demand estimating means obtains at least situation data which is input from the input means.

11. The interface device according to claim 1,

wherein the unit to be operated has assignment result display means for displaying a result of assignment made by the assigning means.

12. The interface device according to claim 1, further comprising

process object display means for displaying one of the contents items selected as an object to be processed by the process object selecting means.

13. The interface device according to claim 1,

wherein the unit to be operated is realized as an electronic object on a display.

14. The interface device according to claim 13, further comprising

display form setting means for setting a display form of the electronic object in accordance with a demand estimated by the demand estimating means.

15. The interface device according to claim 1,

wherein three units to be processed are provided.

16. An interface device having at least one unit to be operated which is used to select one of a plurality of contents items to be processed, comprising:

demand estimating means of obtaining situation data for grasping a situation of a user and estimating a demand of the user based on the situation data;

contents recommendation order setting means for setting a contents recommendation order of the contents items in accordance with a demand estimated by the demand estimating means;

assigning means for associating a predetermined contents item with the unit to be operated in accordance with the contents recommendation order set by the contents recommendation order setting means, wherein the predetermined contents item is high in the contents recommendation order; and

process object selecting means for selecting, as an object to be processed, the predetermined contents item associated with the unit to be operated by the assigning means in response to an operation on the unit to be operated.

17. An inferring system of making an inference by using a rule expressed in an If-Then form including a conditional clause and a dependent clause, the inferring system comprising:

rule storing means for storing a rule group that includes a plurality of rules, wherein, in each of the rules, a linguistic or numerical condition is described as the conditional clause for one or more of a plurality of preset situation attributes and a scoring vector is described as the dependent clause to have a degree of a demand as a component for each of a plurality of preset demand attributes;

scoring vector extracting means for obtaining situation data for grasping a situation, determining whether a conditional clause of a rule stored in the rule storing means is sufficient or not based on the situation data, and extracting a scoring vector as a component of the depending clause of each of rules determined to have sufficient conditional clauses;

demand vector generating means for generating a demand vector having, as a component, a degree of a demand for each of the demand attributes in a state generally grasped from the situation data by performing a process of cumulating the scoring vectors extracted by the scoring vector extracting means; and

inference result generating means for generating an inference result based on the demand vector generated by the demand vector generating means.

18. The inferring system according to claim 17,

wherein a rule group stored in the rule storing means includes a one-dimensional rule in which a linguistic or numerical condition for a single situation attribute is described in the conditional clause.

19. The inferring system according to claim 17,

wherein a rule group stored in the rule storing means includes a hierarchical rule in which a linguistic or numerical condition for more than one of the situation attributes is described in the conditional clause.

20. The inferring system according to claim 17,

wherein a plurality of rule groups are stored in the rule storing means, and

the scoring vector extracting means selects a rule group to be used in accordance with the situation data.

21. The inferring system according to claim 17,

wherein the demand vector generating means performs weighed addition on the scoring vector as the cumulating process.

22. The inferring system according to claim 17,

wherein a drivable application is associated with the demand attribute.

23. The inferring system according to claim 17,

wherein an estimated desire of a user is associated with the demand attribute.

24. The inferring system according to claim 23,

wherein the demand vector generating means includes attribute converting means for converting a demand vector having, as the demand attribute, the desire of the user obtained by the cumulating process into a demand vector having a drivable application as the demand attribute.

25. The inferring system according to claim 17,

wherein the scoring vector is set based on a viewpoint of an average user,

wherein the situation data includes at least viewpoint data indicative of a viewpoint of each user, and

wherein the demand vector generating means includes viewpoint converting means for converting a demand vector obtained by the cumulating process into a demand vector in which the viewpoint of the user is reflected based on the viewpoint data.

26. The inferring system according to claim 25,

wherein the viewpoint converting means converts the demand vector by using a coordinate conversion matrix and a translation vector.

27. The inferring system according to claim 17,

wherein initial data of the scoring vector is obtained by totaling evaluations of attribute values based on subjective determinations by a large number of users and statistically averaging the evaluations.

28. The inferring system according to claim 17,

wherein initial data of the scoring vector is obtained by converting subjective empirical rules made by a small number of users into numerical data.

29. The inferring system according to claim 17, further comprising

initial data setting means for setting initial data of the scoring vector.

30. The inferring system according to claim 29,

wherein the initial data setting means sets, as the initial data, input data from an outside or a template selected by an external operation from a preset template group.

31. The inferring system according to claim 29,

wherein the initial data setting means includes initial data generating means for generating initial data of the scoring vector by inference based on a user profile in which at least a preference of the user is described.

32. The inferring system according to claim 29,

wherein, when the rule group is classified into a plurality of partial rule groups constructed by rules in each of which a condition of a same situation attribute is described in the conditional clause and initial data of a scoring vector is set in a certain rule, the initial data setting means includes initial data transferring means for transferring the same initial data to scoring vectors of other rules belonging to a same partial rule group to which the certain rule belongs.

33. The inferring system according to claim 17, further comprising

inference characteristic correcting means for correcting an inference characteristic of the system based on feedback information to an inference result generated by the inference result generating means.

34. The inferring system according to claim 33,

wherein the feedback information is information related to a same user.

35. The inferring system according to claim 33,

wherein the feedback information is information related to another user.

36. The inferring system according to claim 33,

wherein when a preset correction condition is satisfied, the inference characteristic correcting means uses, as the feedback information, a demand vector used to generate an inference result by the inference result generating means, and response data indicative of a response of a user to whom the inference result was presented.

37. The inferring system according to claim 36, further comprising

history storing means for storing a history of the feedback information.

38. The inferring system according to claim 36,

wherein when a difference equal to or larger than a preset threshold value exists between an operation vector generated from the response data and a demand vector associated with the response data in accordance with the feedback information or when it is statistically recognized that a difference equal to or larger than the threshold value exists between the vectors based on history of the feedback information in a preset period, it is regarded that the correction condition is satisfied, and the inference characteristic correcting means corrects the inference characteristic based on a target rule as the rule related to the demand vector satisfying the correction condition.

39. The inferring system according to claim 38,

wherein the inference characteristic correcting means corrects the inference characteristic by changing a value of a scoring vector as a component of the dependent clause of the target rule.

40. The inferring system according to claim 38,

wherein the inference characteristic correcting means corrects the inference characteristic by changing a linguistic or numerical condition as a component of the conditional clause of the target rule.

41. The inferring system according to claim 38,

wherein the inference characteristic correcting means corrects the inference characteristic by adding a new rule obtained by sub-dividing the linguistic or numerical condition as a component of the conditional clause of the target rule.

42. The inferring system according to claim 38,

wherein the inference characteristic correcting means corrects the inference characteristic by setting a new situation attribute based on the target rule and adding a rule corresponding to the situation attribute.

43. The inferring system according to claim 38,

wherein at the time of generating the demand vector by the demand vector generating means, the inference characteristic correcting means corrects the inference characteristic by changing a value of a parameter used for a scoring vector as a component of a dependent clause of the target rule.

44. The inferring system according to claim 38,

wherein the situation data obtained by the scoring vector extracting means includes a user profile in which at least a preference of a user is described, and

wherein the inference characteristic correcting means corrects the inference characteristic by adding or changing description of the user profile.

45. The inferring system according to claim 17, further comprising:

response detecting means for detecting a response from a user to whom an inference result generated by the inference result generating means is presented; and

rule enhancing means, when the response detected by the response detecting means is an affirmative response to the inference result, for setting a rule related to a demand vector used to obtain the inference result as a rule to be enhanced, and enhancing the rule to be enhanced.

46. The inferring system according to claim 45,

wherein when neighborhood of a conditional clause of the rule to be enhanced is able to be defined, the rule enhancing means also sets a rule having a conditional clause included in the neighborhood as an object to be enhanced.

47. The inferring system according to claim 45,

wherein the rule enhancing means enhances the rule to be enhanced by changing a parameter used at the time of generating the demand vector from a scoring vector as a component of a dependent clause of the rule to be enhanced by the demand vector generating means.

48. The inferring system according to claim 45,

wherein the rule enhancing means enhances the rule to be enhanced by increasing a value of a scoring vector as a component of a dependent clause of the rule to be enhanced.

49. A method of visually expressing a rule group that includes a plurality of rules in each of which a linguistic or numerical condition for at least one of a plurality of preset situation attributes is described in a conditional clause, and a scoring vector having, as a component, a degree of a demand for each of a plurality of preset demand attributes is described,

the method comprising:

a step of associating two of the situation attributes with a two-dimensional address for specifying each of tile images two-dimensionally arranged; and

a step of associating three of the demand attributes with three primary colors expressing colors of the tile images.