US5819245A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Method of organizing data into a graphically oriented format
Assignee: Motorola Solutions Inc
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Filing: 1995-09-05
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Granted: 1998-10-06
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Expires: 2015-09-05
Abstract
Abstract A neural network (10) organizes the data items into a graphically oriented format by retrieving data items from a database (68) where each data item has a plurality of attributes. The neural network is organized (102) such that data items having similar attributes are assigned to neurons located closer together. The neurons of the neural network are matched (104) with the data items from the database and stored in a cross reference table. The cross reference table is displayed (106) on a computer screen (108) in a graphical format so that user visually relates the food items and sees the similarities and differences in their attribute data by the proximity of the data items to one another. The graphic format allows easy visual interpretation of the data items. For large databases, multiple neural networks (110, 112) can be organized hierarchically.
Inventors
- 👤 William M. Peterson
- 👤 Robert H. Leivian
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-04 09:59
CPC Classifications
G; G06; G06N; G06N3/00; G06N3/02; G06N3/04; G06N3/0499
Claims Analysis
Total Claims: 30
Claim 1
Independent Claim
146 words
A computer implemented method of organizing data into a graphically oriented format, comprising the steps of: retrieving data items from a database where said data items each have a plurality of attributes; training synaptic elements of a neural network with said data items so that said data items having similar attributes are assigned to a neighborhood of neurons in said neural network; identifying a closest match between said data items from said database and said neurons of said neural network by comparing said plurality of attributes of said data items with trained values of said synaptic elements of said neurons of said neural network; storing said closest match in a first cross reference table; and displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 2
Dependent Claim
146 words
A computer implemented method of organizing data into a graphically oriented format, comprising the steps of: retrieving data items from a database where said data items each have a plurality of attributes; training synaptic elements of a neural network with said data items so that said data items having similar attributes are assigned to a neighborhood of neurons in said neural network; identifying a closest match between said data items from said database and said neurons of said neural network by comparing said plurality of attributes of said data items with trained values of said synaptic elements of said neurons of said neural network; storing said closest match in a first cross reference table; and displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 3
Dependent Claim
87 words
The method of claim 1 wherein said step of training includes the steps of: applying elements of an input signal vector representing said plurality of attributes of one of said data items to said neurons of said neural network; identifying one of said neurons as having synapses that are most closely matched to said elements of said input signal vector; and adjusting said synapses of said one of said neurons to more closely match said elements of said input signal vector according to a predetermined learning rule.
Claim 4
Dependent Claim
47 words
The method of claim 2 wherein said step of matching includes the steps of: comparing said synapses of one of said neurons to said plurality of attributes of said data items; and identifying one of said data items that most closely matches said one of said neurons.
Claim 5
Dependent Claim
60 words
The method of claim 2 wherein said step of matching includes the steps of: applying said input signal vector representing said plurality of attributes of said one of said data items to said neurons of said neural network; and identifying one of said neurons as having synapses that are most closely matched to said elements of said input signal vector.
Claim 6
Dependent Claim
36 words
The method of claim 1 wherein said step of displaying includes the steps of: forming graphical icons representative of said data items; and selecting one of said graphical icons to display attributes of said data items.
Claim 7
Dependent Claim
29 words
The method of claim 5 wherein said step of forming graphical icons includes the steps of forming said graphical icons by illustrating natural physical embodiments of said data items.
Claim 8
Dependent Claim
39 words
The method of claim 5 wherein said step of forming graphical icons includes the steps of forming said graphical icons by illustrating abstract embodiments of said data items with varying sizes and shapes for each of said data items.
Claim 9
Dependent Claim
91 words
The method of claim 1 further including the steps of: retrieving data items from a database at a second point in time; training said neural network with said plurality of attributes of said data items from said second point in time; matching said neurons of said neural network with said data items from said database and storing matches in a second cross reference table; and displaying said first and second cross reference tables in chronological sequence in a graphical format to present similarities and differences between said data items over time.
Claim 10
Independent Claim
132 words
A system for organizing data into a graphically oriented format, comprising: means for training memory elements of an organization map with attributes of data items so that said data items having similar attributes are assigned to a neighborhood of processing elements in said organization map; means for identifying a closest match between said data items and said processing elements of said organization map by comparing said attributes of said data items with trained values of said memory elements of said processing elements of said projection map; means for storing said closest match in a first cross reference table; and means for displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 11
Independent Claim
132 words
A system for organizing data into a graphically oriented format, comprising: means for training memory elements of an organization map with attributes of data items so that said data items having similar attributes are assigned to a neighborhood of processing elements in said organization map; means for identifying a closest match between said data items and said processing elements of said organization map by comparing said attributes of said data items with trained values of said memory elements of said processing elements of said projection map; means for storing said closest match in a first cross reference table; and means for displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 12
Dependent Claim
84 words
The system of claim 9 wherein said means for training includes: means for applying elements of an input signal vector representing attributes of one of said data items to said processing elements of said organization map; means for identifying one of said processing elements as having weights that are most closely matched to said elements of said input signal vector; and means for adjusting said weights of said one of said processing elements to more closely match said elements of said input signal vector.
Claim 13
Dependent Claim
126 words
A computer implemented method of organizing data into a graphically oriented format, comprising the steps of: training processing elements of a projection map with attributes of data items so that said data items having similar attributes are assigned to a neighborhood of said processing elements in said projection map; identifying a closest match between said data items and said processing elements of said projection map by comparing said attributes of said data items with trained values of said processing elements of said projection map; storing said closest match in a first cross reference table; and displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar date items in proximity to one another in a display area.
Claim 14
Dependent Claim
126 words
A computer implemented method of organizing data into a graphically oriented format, comprising the steps of: training processing elements of a projection map with attributes of data items so that said data items having similar attributes are assigned to a neighborhood of said processing elements in said projection map; identifying a closest match between said data items and said processing elements of said projection map by comparing said attributes of said data items with trained values of said processing elements of said projection map; storing said closest match in a first cross reference table; and displaying said first cross reference table in a graphical format to present similarities between said data items by positioning similar date items in proximity to one another in a display area.
Claim 15
Dependent Claim
81 words
The method of claim 11 wherein said step of organizing includes the steps of: applying elements of an input signal vector representing attributes of one of said data items to said processing elements of said projection map; identifying one of said processing elements as having weights that are most closely matched to said elements of said input signal vector; and adjusting said weights of said one of said processing elements to more closely match said elements of said input signal vector.
Claim 16
Dependent Claim
49 words
The method of claim 12 wherein said step of matching includes the steps of: comparing said weights of one of said processing elements to each of said attributes of said data items; and identifying one of said data items that most closely matches said one of said processing elements.
Claim 17
Dependent Claim
60 words
The method of claim 12 wherein said step of matching includes the steps of: applying said input signal vector representing said attributes of said one of said data items to said processing elements of said projection map; and identifying one of said processing elements as having weights that are most closely matched to said elements of said input signal vector.
Claim 18
Dependent Claim
34 words
The method of claim 11 wherein said step of displaying includes the steps of: forming graphical icons representative of said data items; and selecting said graphical icons to display attributes of said data items.
Claim 19
Dependent Claim
29 words
The method of claim 15 wherein said step of forming graphical icons includes the steps of forming said graphical icons by illustrating natural physical embodiments of said data items.
Claim 20
Dependent Claim
40 words
The method of claim 15 wherein said step of forming graphical icons includes the steps of forming said graphical icons by illustrating abstract embodiments of said data items with varying sizes, shapes or coloring for each of said data items.
Claim 21
Dependent Claim
82 words
The method of claim 11 further including the steps of: providing data items at a second point in time; organizing said projection map with said attributes of said data items from said second point in time; matching said processing elements of said projection map with said data items and storing matches in a second cross reference table; and displaying said first and second cross reference tables in chronological sequence in a graphical format to present similarities between said data items over time.
Claim 22
Dependent Claim
56 words
The method of claim 11 further including the steps of: selecting primary items from a first level module; passing attributes of said primary items to a second level module to select secondary items in said second level module; and passing attributes of said secondary items in said second level module back to said first level module.
Claim 23
Dependent Claim
40 words
The method of claim 19 further including the steps of: aggregating said attributes of said secondary items for one primary item with attributes of said secondary items with a second primary item; and providing said aggregation with said primary items.
Claim 24
Dependent Claim
37 words
The method of claim 11 wherein said step of displaying includes the steps of: forming graphical icons representative of said data items; and displaying said graphical icons to present the similarities between attributes of said data items.
Claim 25
Dependent Claim
19 words
The method of claim 21 wherein said graphical icons are arranged in a grid array in the display area.
Claim 26
Dependent Claim
48 words
The method of claim 11 wherein said step of displaying includes the steps of: forming graphical icons representative of said data items; and displaying said graphical icons of similar data items in proximity to each other and said graphical icons of dissimilar data items distant from each other.
Claim 27
Independent Claim
114 words
A method of organizing data into a graphically oriented format, comprising the steps of: training synaptic elements of a neural network with attributes of data items from a database so that said data items having similar attributes are assigned to a neighborhood of neurons in said neural network; identifying a closest match between said data items and neurons of said neural network by comparing said attributes of said data items with trained values of said synaptic elements of said neurons of said neural network; and displaying said closest match in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 28
Independent Claim
114 words
A method of organizing data into a graphically oriented format, comprising the steps of: training synaptic elements of a neural network with attributes of data items from a database so that said data items having similar attributes are assigned to a neighborhood of neurons in said neural network; identifying a closest match between said data items and neurons of said neural network by comparing said attributes of said data items with trained values of said synaptic elements of said neurons of said neural network; and displaying said closest match in a graphical format to present similarities between said data items by positioning similar data items in proximity to one another in a display area.
Claim 29
Dependent Claim
48 words
The method of claim 24 wherein said step of displaying includes the steps of: forming graphical icons representative of said data items; and displaying said graphical icons of similar data items in proximity to each other and said graphical icons of dissimilar data items distant from each other.
Claim 30
Dependent Claim
19 words
The method of claim 25 wherein said graphical icons are arranged in a grid array in the display area.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2001-10-05 | 2002-04-06 | 2002-10-06 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2005-10-05 | 2006-04-06 | 2006-10-06 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2009-10-05 | 2010-04-06 | 2010-10-06 | $7700.00 | Window Closed / Lapsed |