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.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11908220. Although the claims at issue are not identical, they are not patentably distinct from each other because other than the single vs double database, they recite similar limitations.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a mental process without significantly more. Claim 1 recites:
“an image database comprising delivery information of a plurality of distribution items, the image database including images and corresponding delivery points for the plurality of distribution items; and “, which is directed to an additional element which is a generic computer component recited at a high level of generality and is well-understood, routine and conventional. See MPEP 2106.05(d)
“one or more processors in data communication with the image database, wherein the one or more processors are configured to :” , which is directed to an additional element which is a generic computer component recited at a high level of generality and is well-understood, routine and conventional. See MPEP 2106.05(d)
“identify a first geographical area; “which is directed to a mental process. For example a person can identify a state or geographic area by simple observation/identification. See MPEP2106.04(a)(2).
“identify a first set delivery information in the image database, the first set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified first geographical area; “, which is directed to a mental process. For example a person can identify/select from a list of items associate with a given geographic area (state) mentally. See MPEP2106.04(a)(2).
“train, using the images of the first set of delivery information, one or more machine learning models to recognize a first geographical area component corresponding to the identified first geographical area; “, which is directed to an additional element which is a generic computer component recited at a high level of generality and is well-understood, routine and conventional. See MPEP 2106.05(d).
“identify a second geographical area which is within the first geographical area;” , which is directed to a mental process. For example a person can identify a city within a state or geographic area by simple observation/identification. See MPEP2106.04(a)(2).
“identify from the first set of delivery information, a second set of delivery information, the second set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified second geographical areas” , which is directed to a mental process. For example a person can identify/select from a list of items associate with a given geographic area (city) mentally. See MPEP2106.04(a)(2).
“train, using the images of the second set of delivery information, the one or more machine learning models to recognize a second geographical area component corresponding to the identified second geographical area.”, which is directed to an additional element which is a generic computer component recited at a high level of generality and is well-understood, routine and conventional. See MPEP 2106.05(d).
This judicial exception is not integrated into a practical application. As explained above, The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 11 is rejected under similar grounds as claim 1.
The Examiner recognizes the improvement of 2ms vs 100ms improvement in speed, shown in paragraphs 63-64 and 122. But how this improvement was accomplished using non-conventional techniques was not specifically claimed. The Examiner recommends the following suggestions:
1) Incorporate some type of physical machine which physically sorts mail based on the neural network (practical application). See paragraph 55-58.
2) Incorporate non-conventional training architecture, such as done in the parent case. OR
3) Incorporate an inference limitation with the specific improvement (without OCR).
Claims 2-10 and 12-20 are rejected as failing to cure deficiencies of the base claim.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “delivery points”.
Paragraph 64 recites “automatically recognizing geographical area information, such as delivery point information, on an item without using an OCR process.”, this defines delivery point information as “geographical area information” which comprises a state, a city, a street, and a street number(see paragraph 7)
Paragraph 65 recites “A distribution network, such as the USPS can generate a database, repository or vast store of images of addresses or delivery points on items,”, which defines delivery points as images of addresses.
Paragraph 86 recites “. In some embodiments, the image from the optical scanner 210 may have been subjected to an OCR process in order to recognize or interpret writing, letters, words, numbers, etc., thereon, such as a delivery point, return address, etc.”, which defines delivery point as writing, letters, words, numbers etc.
Paragraph 87 recites “This may occur by performing an OCR process on the received or retrieved image, or may be done by obtaining the image and reading metadata thereof which includes delivery point information, or by reading delivery point information associated with the image”, which defines metadata as delivery point information .
Paragraph 103 recites “. To generate the large number of images, an automated system can automatically generate a large number of images depicting known geographical area information, such as delivery point information.” this defines delivery point information as “geographical area information” which comprises a state, a city, a street, and a street number(see paragraph 7)
Due to the multiple definitions of delivery point, a POSITA would not recognize what Applicant has invented.
Claim 11 is rejected under similar grounds as claim 1.
Claims 2-10 and 12-20 are rejected as dependent upon a rejected claim.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “delivery point”. The specification appears to have multiple definitions of the term “delivery point”. When the claim recites “delivery point” it is not clear which definition applicant is intending. Does delivery point mean the complete address, an element of the address or an image of the complete/partial address. See 112 1st rejection above.
Claim 11 is rejected under similar grounds as claim 1.
Claim 1 recites “ a plurality of distribution items”. Later in the claim recites “the plurality of items”. It is not clear if the plurality of items refers to the distribution items or is an independent article. Further correction is required. See also claims 2-4.
Claim 11 recites “a plurality of items”. Claim 12 and 20 recite a “plurality of distribution items”. It is not clear if the plurality of items refers to the distribution items or is an independent article. Further correction is required.
Claims 1-20 has uses the phrase a XXX area followed by the XXX areas. *Note : Singular to Plural This error is repeated for the second geographical area, third geographic area and fourth geographical area. Further correction is required in claims 1,3,4,11,13 and 14.
Claim 8 and 18 recites “8. The system of claim 4, wherein the fourth geographical area is a first street number of a plurality of street numbers within third geographical area, and wherein the fourth geographical area component is an identifier of the first street.” The definitions conflict.
Claims 2-10 and 12-20 are rejected as dependent upon a rejected claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over NTEX (11,250,452) in view of LMCO (5754671).
NTEX discloses A system for identifying delivery points on distribution items, the system comprising:
a heirarchial ML training architecture for address classification and sorting,
an image database comprising delivery information of a plurality of distribution items, the image database including NTEX, Col. 13 lines 50-67, “The database 116 provides storage location to the one or more pre-defined points of interests, the one or more pre-defined localities, the one or more pre-defined sub-localities, the address data, the one or more points of interests, the one or more localities, the one or more sub-localities, and the like. In an embodiment of the present disclosure, the database 116 provides storage location to all the data and information required by the address classification and sorting system 112.”)
one or more processors in data communication with the image database(NTEX,Fig. 4), wherein the one or more processors are configured to:
identify a first geographical area; identify a first set delivery information in the image database, the first set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified first geographical area; train, using the images of the first set of delivery information, one or more machine learning models to recognize a first geographical area component corresponding to the identified first geographical area; identify a second geographical area which is within the first geographical area; identify from the first set of delivery information, a second set of delivery information, the second set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified second geographical areas; and train, using the images of the second set of delivery information, the one or more machine learning models to recognize a second geographical area component corresponding to the identified second geographical area. (NTEX, Col. 10 Lines 12-49, “(26) The address classification and sorting system 112 logically partitions the geographical region to train the address classification and sorting system 112. The address classification and sorting system 112 is trained with all available addresses of the one or more facilities. In addition, the address classification and sorting system 112 is continuously trained with the address data of newer addresses. The address classification and sorting system 112 is provided with one or more pre-defined points of interests. In general, points of interests are specific point locations that someone may find useful or interesting. In an example, the points of interests are identified from the unstructured address information to figure out location of the facility. In another example, the points of interests are famous landmarks that help in finding out accurate location of the facility. The address classification and sorting system 112 logically partitions the geographical region based on the one or more pre-defined points of interests. The address classification and sorting system 112 segments the one or more pre-defined points of interests into one or more pre-defined localities and sub-localities. The one or more pre-defined localities and sub-localities help to determine the logical zone under which the address of the facility should fall. The logical zone is determined such that movement of the entities from the processing center 108 to the delivery address takes the shortest route and the least amount of time possible. The one or more pre-defined points of interests are segmented into the one or more pre-defined localities. Further, the one or more pre-defined localities are segmented into one or more pre-defined sub-localities. In an embodiment of the present disclosure, the address classification and sorting system 112 is trained to identify accurate location of the delivery address based on the one or more pre-defined points of interests. In an embodiment of the present disclosure, the address classification and sorting system 112 is trained to logically partition the geographical region into the one or more logical zones based on the delivery address of the one or more entities.”, discloses segmenting an address into a plurality of geographical areas and training a graph based machine learning algorithm using these plurality of geographical areas.)
NTEX discloses acquiring an image, OCR’ing the image and processing the OCR’d values through the algorithm. Thus NTEX discloses text based on images of addresses and delivery points, but not the images itself.
LMCO discloses using “word Images” (LMCO, Abstract, “A method of cursive address recognition of mail pieces using adaptive dictionary management is provided which includes creating a plurality of word databases containing the most frequently observed words in a particular portion of an address block derived from training data. Word images from various portions of the address block are extracted and the word images are compared to the database corresponding to the appropriate portion of the address block using a cursive word recognition engine. The search order of the word databases are updated based on the frequency of occurrence of recognized words in a predetermined number of previously evaluated addresses.” images of cursive text; See also Col. 5 Lines 12-37) and determining the delivery location.
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to replace the text of NTEX with the word images of LMCO.
The suggestion/motivation for doing so would have been to recognize cursive text.
Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine NTEX with LMCO to obtain the invention as specified in claim 1.
NTEX in view of LMCO discloses 2. The system of claim 1, wherein the corresponding delivery points have been previously determined through optical character recognition of the images of the plurality of distribution items. (see claim 1)
NTEX in view of LMCO discloses 3. The system of claim 1, wherein the one or more processors are further configured to:identify a third geographical area which is within the second geographical area; identify from the second set of delivery information, a third set of delivery information, the third set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified third geographical areas; and train, using the images of the third set of delivery information, one or more machine learning models to recognize a third geographical area component corresponding to the identified third geographical area. (see claim 1)
NTEX in view of LMCO discloses 4. The system of claim 3, wherein the one or more processors are further configured to:identify a fourth geographical area which is within the third geographical area; identify from the third set of delivery information, a fourth set of delivery information, the fourth set of delivery information comprising images and corresponding delivery points for items of the plurality of items that were delivered to delivery points within the identified fourth geographical areas; and train, using the images of the fourth set of delivery information, one or more machine learning models to recognize a fourth geographical area component corresponding to the identified fourth geographical area. (see claim 1)
NTEX in view of LMCO discloses 5. The system of claim 1, wherein the first geographical area is a state, and wherein the first geographical area component is an identifier of the state. (NTEX, Col. 9 Lines 42-63, “In an example, the geographical region includes an area, colony, sector, village, tehsil, city, state, town, country, continent, union territory or combination thereof. The one or more logical zones are simply the one or more sub-regions of the geographical region. ”)
NTEX in view of LMCO discloses 6. The system of claim 1, wherein the second geographical area is a first city of a plurality of cities within the first geographical area, and wherein the second geographical area component is an identifier of the first city. (NTEX, Col. 9 Lines 42-63, “In an example, the geographical region includes an area, colony, sector, village, tehsil, city, state, town, country, continent, union territory or combination thereof. The one or more logical zones are simply the one or more sub-regions of the geographical region. ”)
NTEX in view of LMCO discloses 7. The system of claim 3, wherein the third geographical area is a first street of a plurality of streets within the second geographical area, and wherein the third geographical area component is an identifier of the first street. (NTEX, Col. 6 Lines 37-58, “The address is used to give exact location of a facility, building, apartment, a plot and other structure. In general, the location is provided using political boundaries and street names as references along with other identifiers such as house number, apartment numbers, blocks and the like. The address includes the house number, name of the road, name of the town where a person lives or work, street name and the like. In an example, the receiver address is accurate and exact location where the facility is situated and where the entity is intended to be delivered.”)
NTEX in view of LMCO discloses 8. The system of claim 4, wherein the fourth geographical area is a first street number of a plurality of street numbers within third geographical area, and wherein the fourth geographical area component is an identifier of the first street. (NTEX, Col. 6 Lines 37-58, “he address is used to give exact location of a facility, building, apartment, a plot and other structure. In general, the location is provided using political boundaries and street names as references along with other identifiers such as house number, apartment numbers, blocks and the like. The address includes the house number, name of the road, name of the town where a person lives or work, street name and the like. In an example, the receiver address is accurate and exact location where the facility is situated and where the entity is intended to be delivered.”)
NTEX in view of LMCO discloses 9. The system of claim 1, further comprising a reader configured to capture the delivery information of the plurality of distribution items. (see the combination of references in claim 1)
NTEX in view of LMCO discloses 10. The system of claim 9, wherein the one or more processors are configured to:extract the images and corresponding delivery points for the plurality of distribution items from the captured delivery information; and store the images and corresponding delivery points for the plurality of distribution items in the image database. (see the combination of references in claim 1, where the combination teaches the specific output of images and delivery points stored together)
Claims 11-20 are rejected under similar grounds as claims 1-10.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GANDHI THIRUGNANAM whose telephone number is (571)270-3261. The examiner can normally be reached M-F 8:30-5PM.
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/GANDHI THIRUGNANAM/ Primary Examiner, Art Unit 2672