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Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 1 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 10,832,656. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of the instant application is similar in scope and content of the patented claim 1 of the patent issued to the same Applicant.
It is clear that all the elements of the application claim 1 are to be found in patented claim 1 (as the application claim 1 fully encompasses patented claim 1). The difference between the application claims and the patent claims lies in the fact that the patent claim includes many more elements and is thus much more specific. Thus the invention of claim 1 of the patent is in effect a “species” of the “generic” invention of the application claim 1. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993). Since application claim 1 is anticipated by claim 1 of the patent, it is not patentably distinct from of the patented claims.
Application No: 18/990,279
Patent No: 10,832,656
1. A computing device comprising: a processor; a non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to: retrieve a digital form comprising a plurality of fields; retrieve a plurality of field definitions associated with the plurality of fields; receive a character string; recognize a plurality of target keywords in the character string; extract a plurality of sub-strings from the character string based on the target keywords; generate a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populate a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; display the populated form; and display a user prompt to identify if any errors are present.
1. A computing device comprising: a processor; non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising the following steps: retrieving a digital form comprising a plurality of fields; retrieving a plurality of field definitions associated with the plurality of fields; generating a character string by applying a speech recognition algorithm to audio data comprising a user's speech; recognizing a plurality of target keywords in the character string; extracting a plurality of sub-strings from the character string based on the target keywords; generating a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form, where each sub-string is analyzed in real-time while the user speaks; and populating a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
2. The computing device of claim 1, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to display the user prompt to identify a field requiring correction.
3. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
4. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a corrected field string.
5. The computing device of claim 4, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and record the result of the evaluation.
6. The computing device of claim 5, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
7. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: receive audio data comprising speech of the user; and generate an audio character string by applying a speech recognition algorithm to the audio data.
8. The computing device of claim 7, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to identify the field needing correction based on the audio character string.
9. The computing device of claim 8, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to extract a corrected field string from the audio character string.
10. The computing device of claim 9, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and record the result of the evaluation.
11. The computing device of claim 10, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
12. A method of operating a computing device, the method comprising: retrieving, by a processor, a digital form comprising a plurality of fields; retrieving, by the processor, a plurality of field definitions associated with the plurality of fields; receiving a character string; recognizing, by the processor, a plurality of target keywords in the character string; extracting, by the processor, a plurality of sub-strings from the character string based on the target keywords; generating, by the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating, by the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; displaying, by a display device, the populated form; and displaying, by the display device, a user prompt to identify if any errors are present.
13. The method of claim 12, further comprising displaying, by the display device, the user prompt to identify a field requiring correction.
14. The method of claim 13, further comprising receiving a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
15. The method of claim 13, further comprising receiving a corrected field string.
16. The method of claim 15, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and recording, by the processor, the result of the evaluation.
17. The method of claim 13, further comprising: receiving audio data comprising speech of the user; and generating, by the processor, an audio character string by applying a speech recognition algorithm to the audio data.
18. The method of claim 17, further comprising identifying, by the processor, the field needing correction based on the audio character string.
19. The method of claim 18, further comprising extracting, by the processor, a corrected field string from the audio character string.
20. The method of claim 19, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and recording the result of the evaluation.
Claims 12 and 17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 11 and 17 of U.S. Patent No. 11,062,695. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 12 and 17 of the instant application is similar in scope and content of the patented claims 1, 11 and 17 of the patent issued to the same Applicant.
It is clear that all the elements of the application claims 12 and 17 are to be found in patented claims 1, 11 and 17 (as the application claims 12 and 17 fully encompasses patented claims 1, 11 and 17). The difference between the application claims and the patent claims lies in the fact that the patent claim includes many more elements and is thus much more specific. Thus the invention of claims 1, 11 and 17 of the patent is in effect a “species” of the “generic” invention of the application claims 12 and 17. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993). Since application claims 12 and 17 is anticipated by claims 1, 11 and 17 of the patent, it is not patentably distinct from of the patented claims.
Application No: 18/990,279
Patent No: 11,060,695
1. A computing device comprising: a processor; a non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to: retrieve a digital form comprising a plurality of fields; retrieve a plurality of field definitions associated with the plurality of fields; receive a character string; recognize a plurality of target keywords in the character string; extract a plurality of sub-strings from the character string based on the target keywords; generate a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populate a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; display the populated form; and display a user prompt to identify if any errors are present.
2. The computing device of claim 1, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to display the user prompt to identify a field requiring correction.
3. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
4. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a corrected field string.
5. The computing device of claim 4, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and record the result of the evaluation.
6. The computing device of claim 5, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
7. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: receive audio data comprising speech of the user; and generate an audio character string by applying a speech recognition algorithm to the audio data.
8. The computing device of claim 7, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to identify the field needing correction based on the audio character string.
9. The computing device of claim 8, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to extract a corrected field string from the audio character string.
10. The computing device of claim 9, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and record the result of the evaluation.
11. The computing device of claim 10, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
12. A method of operating a computing device, the method comprising: retrieving, by a processor, a digital form comprising a plurality of fields; retrieving, by the processor, a plurality of field definitions associated with the plurality of fields; receiving a character string; recognizing, by the processor, a plurality of target keywords in the character string; extracting, by the processor, a plurality of sub-strings from the character string based on the target keywords; generating, by the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating, by the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; displaying, by a display device, the populated form; and displaying, by the display device, a user prompt to identify if any errors are present.
1. A method comprising the steps of: retrieving, via a processor, a digital form comprising a plurality of fields; retrieving, via the processor, a plurality of field definitions associated with the plurality of fields; generating, via the processor, a character string by applying a speech recognition algorithm to audio data comprising a user's speech; recognizing, via the processor, a plurality of target keywords in the character string; extracting, via the processor, a plurality of sub-strings from the character string based on the target keywords; generating, via the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form, where each sub-string is analyzed in real-time while the user speaks; and populating, via the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
11. A method comprising the steps of: retrieving, via a processor, a digital form comprising a plurality of fields; generating a plurality of field definitions associated with the plurality of fields, based on the digital form; generating, via the processor, a character string by applying a speech recognition algorithm to audio data comprising a user's speech; recognizing, via the processor, a plurality of target keywords in the character string; extracting, via the processor, a plurality of sub-strings from the character string based on the target keywords; generating, via the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form, where each sub-string is analyzed in real-time while the user speaks; and populating, via the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
13. The method of claim 12, further comprising displaying, by the display device, the user prompt to identify a field requiring correction.
14. The method of claim 13, further comprising receiving a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
15. The method of claim 13, further comprising receiving a corrected field string.
16. The method of claim 15, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and recording, by the processor, the result of the evaluation.
17. The method of claim 13, further comprising: receiving audio data comprising speech of the user; and generating, by the processor, an audio character string by applying a speech recognition algorithm to the audio data.
17. The method of claim 14, where the method further comprises retrieving, via the processor, the pattern-recognition algorithm.
18. The method of claim 17, further comprising identifying, by the processor, the field needing correction based on the audio character string.
19. The method of claim 18, further comprising extracting, by the processor, a corrected field string from the audio character string.
20. The method of claim 19, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and recording the result of the evaluation.
Claims 1, 7, 11-12 and 17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3-4, 8, 10, 13-15, and 17-20 of U.S. Patent No. 11,062,695. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 7, 11-12 and 17 of the instant application is similar in scope and content of the patented claims 1, 3-4, 8, 10, 13-15, and 17-20 of the patent issued to the same Applicant.
It is clear that all the elements of the application claims 1, 7, 11-12 and 17 are to be found in patented claims 1, 3-4, 8, 10, 13-15, and 17-20 (as the application claims 1, 7, 11-12 and 17 fully encompasses patented claims 1, 3-4, 8, 10, 13-15, and 17-20). The difference between the application claims and the patent claims lies in the fact that the patent claim includes many more elements and is thus much more specific. Thus the invention of claims 1, 3-4, 8, 10, 13-15, and 17-20 of the patent is in effect a “species” of the “generic” invention of the application claims 1, 7, 11-12 and 17. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993). Since application claims 1, 7, 11-12 and 17 is anticipated by claims 1, 3-4, 8, 10, 13-15, and 17-20 of the patent, it is not patentably distinct from of the patented claims.
Application No: 18/990,279
Patent No: 11,705,132
1. A computing device comprising: a processor; a non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to: retrieve a digital form comprising a plurality of fields; retrieve a plurality of field definitions associated with the plurality of fields; receive a character string; recognize a plurality of target keywords in the character string; extract a plurality of sub-strings from the character string based on the target keywords; generate a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populate a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; display the populated form; and display a user prompt to identify if any errors are present.
1. A computing device comprising: a processor; non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising the following steps: retrieving a digital form comprising a plurality of fields; retrieving a plurality of field definitions associated with the plurality of fields; receiving a character string; recognizing a plurality of target keywords in the character string; extracting a plurality of sub-strings from the character string based on the target keywords; generating a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; and populating a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
3. The computing device of claim 1, where the plurality of field definitions further comprises target keywords associated with the plurality of fields in the digital form.
8. A computing device comprising: a processor; non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising the following steps: retrieving a digital form comprising a plurality of fields; generating a plurality of field definitions associated with the plurality of fields, based on the digital form; receiving a character string; recognizing a plurality of target keywords in the character string; extracting a plurality of sub-strings from the character string based on the target keywords; generating a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in a digital form; and populating a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
10. The computing device of claim 8, where the plurality of field definitions further comprises target keywords associated with the plurality of fields in the digital form.
2. The computing device of claim 1, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to display the user prompt to identify a field requiring correction.
3. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
4. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a corrected field string.
5. The computing device of claim 4, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and record the result of the evaluation.
6. The computing device of claim 5, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
7. The computing device of claim 6 where the pattern-recognition algorithm is retrieved from a remote server.
7. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: receive audio data comprising speech of the user; and generate an audio character string by applying a speech recognition algorithm to the audio data.
4. The computing device of claim 1, where analyzing each sub-string for compliance with each of a plurality of field definitions comprises applying a pattern-recognition algorithm to the sub-strings and the field definitions.
8. The computing device of claim 7, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to identify the field needing correction based on the audio character string.
9. The computing device of claim 8, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to extract a corrected field string from the audio character string.
10. The computing device of claim 9, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and record the result of the evaluation.
11. The computing device of claim 10, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
13. The computing device of claim 12, where the method further comprises retrieving the pattern-recognition algorithm.
14. The computing device of claim 13 where the pattern-recognition algorithm is retrieved from a remote server.
12. A method of operating a computing device, the method comprising: retrieving, by a processor, a digital form comprising a plurality of fields; retrieving, by the processor, a plurality of field definitions associated with the plurality of fields; receiving a character string; recognizing, by the processor, a plurality of target keywords in the character string; extracting, by the processor, a plurality of sub-strings from the character string based on the target keywords; generating, by the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating, by the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; displaying, by a display device, the populated form; and displaying, by the display device, a user prompt to identify if any errors are present.
15. A method comprising the steps of: retrieving, via a processor, a digital form comprising a plurality of fields; retrieving, via the processor, a plurality of field definitions associated with the plurality of fields; receiving, via the processor, a character string; recognizing, via the processor, a plurality of target keywords in the character string; extracting, via the processor, a plurality of sub-strings from the character string based on the target keywords; generating, via the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; and populating, via the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions.
17. The method of claim 15, where the plurality of field definitions further comprises target keywords associated with the plurality of fields in the digital form.
13. The method of claim 12, further comprising displaying, by the display device, the user prompt to identify a field requiring correction.
14. The method of claim 13, further comprising receiving a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
15. The method of claim 13, further comprising receiving a corrected field string.
16. The method of claim 15, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and recording, by the processor, the result of the evaluation.
17. The method of claim 13, further comprising: receiving audio data comprising speech of the user; and generating, by the processor, an audio character string by applying a speech recognition algorithm to the audio data.
18. The method of claim 15, where analyzing each sub-string for compliance with each of a plurality of field definitions comprises applying a pattern-recognition algorithm to the sub-strings and the field definitions.
19. The method of claim 18, where the pattern-recognition algorithm is generated using machine learning.
20. The method of claim 18, where the method further comprises retrieving, via the processor, the pattern-recognition algorithm.
18. The method of claim 17, further comprising identifying, by the processor, the field needing correction based on the audio character string.
19. The method of claim 18, further comprising extracting, by the processor, a corrected field string from the audio character string.
20. The method of claim 19, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and recording the result of the evaluation.
Claims 1, 6-12 and 16-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, and 4-20 of U.S. Patent No. 12,183,345. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 6-12 and 16-20 of the instant application is similar in scope and content of the patented claims 1 and 4-20 of the patent issued to the same Applicant.
It is clear that all the elements of the application claims 1, 6-12 and 16-20 are to be found in patented claims 1 and 4-20 (as the application claims 1, 6-12 and 16-20 fully encompasses patented claims 1 and 4-20). The difference between the application claims and the patent claims lies in the fact that the patent claim includes many more elements and is thus much more specific. Thus the invention of claims 1 and 4-20 of the patent is in effect a “species” of the “generic” invention of the application claims 1, 6-12 and 16-20. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993). Since application claims 1, 6-12 and 16-20 is anticipated by claims 1 and 4-20 of the patent, it is not patentably distinct from of the patented claims.
Application No: 18/990,279
Patent No: 12,183,345
1. A computing device comprising: a processor; a non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to: retrieve a digital form comprising a plurality of fields; retrieve a plurality of field definitions associated with the plurality of fields; receive a character string; recognize a plurality of target keywords in the character string; extract a plurality of sub-strings from the character string based on the target keywords; generate a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populate a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; display the populated form; and display a user prompt to identify if any errors are present.
1. A computing device comprising: a processor; non-transient memory operably connected to the processor, the non-transient memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising the following steps: retrieving a digital form comprising a plurality of fields; retrieving a plurality of field definitions associated with the plurality of fields; recognizing a plurality of target keywords in a character string; extracting a plurality of sub-strings from the character string based on the target keywords; generating a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; transmitting the character string and the populated form fields to a remote server; and receiving a validated form from the remote server.
2. The computing device of claim 1, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to display the user prompt to identify a field requiring correction.
3. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
4. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to receive a corrected field string.
5. The computing device of claim 4, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and record the result of the evaluation.
6. The computing device of claim 5, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
12. The computing device of claim 8, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
7. The computing device of claim 2, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: receive audio data comprising speech of the user; and generate an audio character string by applying a speech recognition algorithm to the audio data.
4. The computing device of claim 3 where the method further comprises the following steps: receiving audio data comprising a user's speech; generating the character string by applying a speech recognition algorithm to the audio data; and transmitting the audio data to the remote server with the character string and the populated form fields.
8. The computing device of claim 7, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to identify the field needing correction based on the audio character string.
5. The computing device of claim 4, where being validated by the natural language processing validation engine further comprises confirming that a populated form field value is valid based on the audio data.
9. The computing device of claim 8, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to extract a corrected field string from the audio character string.
6. The computing device of claim 5, where being validated by the natural language processing validation engine further comprises validating the character string against the audio data.
10. The computing device of claim 9, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to: evaluate the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and record the result of the evaluation.
7. The computing device of claim 6, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
8. The computing device of claim 4, where being validated by the natural language processing validation engine further comprises confirming that a populated form field value is valid based on the character string and the audio data.
9. The computing device of claim 5, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
10. The computing device of claim 8, where being validated by the natural language processing validation engine further comprises validating the character string against the audio data.
11. The computing device of claim 10, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
12. The computing device of claim 8, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
11. The computing device of claim 10, wherein the non-transient memory comprises further instructions that, when executed by the processor, cause the processor to transmit the recorded result of the evaluation to a server in association with training a form completion algorithm.
12. The computing device of claim 8, where the method further comprises receiving an updated form completion algorithm from the remote server, where the updated form completion algorithm is based on the audio data, the character string, and the populated form fields.
12. A method of operating a computing device, the method comprising: retrieving, by a processor, a digital form comprising a plurality of fields; retrieving, by the processor, a plurality of field definitions associated with the plurality of fields; receiving a character string; recognizing, by the processor, a plurality of target keywords in the character string; extracting, by the processor, a plurality of sub-strings from the character string based on the target keywords; generating, by the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, wherein each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating, by the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; displaying, by a display device, the populated form; and displaying, by the display device, a user prompt to identify if any errors are present.
13. A method comprising: retrieving, via a processor, a digital form comprising a plurality of fields; retrieving, via the processor, a plurality of field definitions associated with the plurality of fields; recognizing, via the processor, a plurality of target keywords in a character string; extracting, via the processor, a plurality of sub-strings from the character string based on the target keywords; generating, via the processor, a numerical score by analyzing each sub-string for compliance with each of the plurality of field definitions, where each of the plurality of field definitions comprises a field name and a data type and corresponds to one of the plurality of fields in the digital form; populating, via the processor, a plurality of the fields in the digital form based on the numerical score generated during the analysis of each sub-string for compliance with each of the plurality of field definitions; transmitting the character string and the populated form fields to a remote server; and receiving a validated form from the remote server.
13. The method of claim 12, further comprising displaying, by the display device, the user prompt to identify a field requiring correction.
14. The method of claim 13, further comprising receiving a user input from one of a touchscreen and a pointing device to identify the field requiring correction.
15. The method of claim 13, further comprising receiving a corrected field string.
16. The method of claim 15, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires any of replacing, amending, and adding to the existing string; and recording, by the processor, the result of the evaluation.
14. The method of claim 13, where the validated form comprises a plurality of validated form fields, where each validated form field comprises a value that has been validated by a natural language processing validation engine.
15. The method of claim 14, where being validated by the natural language processing validation engine comprises confirming that a populated form field value is valid based on the character string.
17. The method of claim 13, further comprising: receiving audio data comprising speech of the user; and generating, by the processor, an audio character string by applying a speech recognition algorithm to the audio data.
16. The computing device of claim 15 where the method further comprises the following steps: receiving audio data comprising a user's speech; generating, via the processor, the character string by applying a speech recognition algorithm to the audio data; and transmitting the audio data to the remote server with the character string and the populated form fields.
18. The method of claim 17, further comprising identifying, by the processor, the field needing correction based on the audio character string.
17. The method of claim 16, where being validated by the natural language processing validation engine further comprises confirming that a populated form field value is valid based on the audio data.
19. The method of claim 18, further comprising extracting, by the processor, a corrected field string from the audio character string.
18. The method of claim 17, where being validated by the natural language processing validation engine further comprises validating the character string against the audio data.
19. The method of claim 16, where being validated by the natural language processing validation engine further comprises confirming that a populated form field value is valid based on the character string and the audio data.
20. The method of claim 19, further comprising: evaluating, by the processor, the corrected field string against a corresponding existing field string to determine if the corrected field string requires one of replacing, amending, and adding to the existing string; and recording the result of the evaluation.
19. The method of claim 16, where being validated by the natural language processing validation engine further comprises confirming that a populated form field value is valid based on the character string and the audio data.
20. The method of claim 19, where being validated by the natural language processing validation engine further comprises validating the character string against the audio data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see attached form PTO-892.
Muhammedali (US 2017/0330153 A1) teaches search Extraction Matching, Draw Attention-Fit Modality, Application Morphing, and Informed Apply Apparatuses, Methods and Systems (“SEMATFM-AMIA”) that transforms inputs including new job listing introduction inputs, via SEMATFM-AMIA components (e.g., the conductor component, the resume view controller component, the XY paths handler component, the title handler component, the resume librarian component, and the job listing librarian component), into outputs including relevant resume outputs and/or augmented new job listing record outputs. In one embodiment, the SEMATFM-AMIA includes an apparatus, comprising: a memory, a component collection in the memory, and a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory. SEMATFM-AMIA may then receive, in connection with an application to a job, a resume adjustment request, where the request includes one or more raw terms of a resume, one or more normalized terms of the resume, one or more raw terms of a job listing corresponding to the job, and one or more normalized terms of the job listing. SEMATFM-AMIA may load said resume normalized terms and said job listing normalized terms into a joined normalized terms set, and add to a common normalized terms set normalized term members of the joined normalized terms set which meet a count criterion. SEMATFM-AMIA may visit each of one or more normalized term members of the common normalized terms set. After further receiving, adding, visiting, providing and otherwise processing data, SEMATFM-AMIA may receive, from the resume adjuster component, a request to formulate the adjusted resume record, wherein said record formulation request includes specification of the resume and substitution information, and formulate the adjusted resume record which substitutes each of user-selected resume raw terms with a corresponding user-selected job listing raw term, wherein the formulation includes accessing one or more stores.
Neels et al., (US 2017/0140039 A1) teach certain system and method embodiments for generating reports from unstructured data. In one embodiment, a method can include identifying events matching criteria of an initial search query (each of the events including a portion of raw machine data that is associated with a time), identifying a set of fields, each field defined for one or more of the identified events, causing display of an interactive graphical user interface (GUI) that includes one or more interactive elements enabling a user to define a report for providing information relating to the matching events (each interactive element enabling processing or presentation of information in the matching events using one or more fields in the identified set of fields), receiving, via the GUI, a report definition indicating how to report information relating to the matching events, and generating, based on the report definition, a report including information relating to the matching events.
Miller et al., (US 2017/0139887 A1) teach formulating and refining field extraction rules that are used at query time on raw data with a late-binding schema. The field extraction rules identify portions of the raw data, as well as their data types and hierarchical relationships. These extraction rules are executed against very large data sets not organized into relational structures that have not been processed by standard extraction or transformation methods. By using sample events, a focus on primary and secondary example events help formulate either a single extraction rule spanning multiple data formats, or multiple rules directed to distinct formats. Selection tools mark up the example events to indicate positive examples for the extraction rules, and to identify negative examples to avoid mistaken value selection. The extraction rules can be saved for query-time use, and can be incorporated into a data model for sets and subsets of event data.
Kinsely et al. (US 2015/0039651 A1) teach a field extraction template that simplifies the creation of field extraction rules by providing a user with a set of field names commonly assigned to a certain type of data, as well as guidance on how to extract values for those fields. These field extraction rules, in turn, facilitate access to certain "chunks" of the data, or to information derived from those chunks, through named fields. A field extraction template comprises at least a set of field names and ordering data for the field names. The ordering data indicates index positions that are associated with at least some of the field names. A delimiter is specified for splitting data items into arrays of chunks. The chunk of a data item that belongs to a given field name is the chunk whose position within the item's array of chunks is equivalent to the index position associated with the given field name.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VIJAY B CHAWAN whose telephone number is (571)272-7601. The examiner can normally be reached 7-5 Monday thru Thursday.
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/VIJAY B CHAWAN/Primary Examiner, Art Unit 2658
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