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 .
DETAILED ACTION
The instant application having Application No. 19/219,366 filed on 05/27/2025 in which claims 1-30 are pending in the application, all of which are ready for examination by the examiner.
Priority
This application is a CON of 18/427,450 filed on 01/30/2024 which is a CON of 17/973,389 filed on 10/25/2022 PAT 11,922,475 which is a CON of 14/656,171 filed on 03/12/2015 PAT 11,514,496 which is a CIP of 13/951,248 filed on 07/25/2013 ABN and is a CIP of 13/951,244 filed on 07/25/2013 PAT 9,047,614 and claims benefit of 61/952,029 filed on 03/12/2014 and claims benefit of 61/952,004 filed on 03/12/2014.
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 1-30 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims 1 and 16 recite identifying a first statistical pattern in a first analysis result from the set of analysis results for the selected product by performing statistical analysis on the product information and the analysis results; in which the first statistical pattern is a statistical pattern between two or more types of data included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes: a social metric, an identification of which product in a sub-set of products leads or follows other products in the sub-set of products in terms of price changes, a demand metric based at least in part on visitors record generated from webpage traffic to one or more online stores at which the product is available, and in which the demand metric is stored in the database coupled to the computer, and a reach of the product in terms of the number of people who visit an online sales venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product, and in which the social metric is stored in a database coupled to the computer; identifying a second statistical pattern in the second analysis result.
The limitations of identifying…, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “system…,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “system…,” “of “identifying…,” in the context of these claims encompass the user manually identifying statistical pattern. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – receiving…, accessing…, generating…, transmitting…, alert…, executing…. The “accessing”, “generating”, and “alert” limitations amount to mere instructions to apply an exception (see MPEP 2106.05f). The “receiving”, “executing” and “transmitting” limitations are insignificant extra-solution activity (mere data gathering, outputting, please see MPEP 2106.05g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. “Accessing”, “generating”, and “alert” amount to mere instructions to apply an exception (see MPEP 2106.05f). The additional elements of “receiving”, “executing” and “transmitting” are a well-understood, routine, and conventional activity (storing or data gathering, outputting, see MPEP 2106.05d). The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 2 and 17 recite the first user selection further comprises at least one of a user list and a user favorite. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 3 and 18 recite the user list comprises a custom list or a smart list. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 4 and 19 recite the smart list is created upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product information and at least one criterion for limiting the first analysis result presented in relation to the user list, and in which the custom list comprises a list of products provided by the user. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 5 and 20 recite comparing the second analysis result relating to the second user selection to the first analysis result, and making a first recommendation to the user based on the comparison of the first and second analysis results. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., comparing, making) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 6 and 21 recite the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of: a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the product sold by the first vendor or the product sold by the second vendor, and a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., add, remove, charge, increase, decrease) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 7 and 22 recite determining if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommending to the user that the product sold by the first vendor or the product sold by the second vendor be removed from inventory. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., determining, recommending) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 8 and 23 recite the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and recommending that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., recommending) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 9 and 24 recite receiving from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identifying the two or more products as substitutes for each other. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., receiving, identifying) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 10 and 25 recite receiving an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., receiving) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 11 and 26 recite the user-specified alarm setting comprises at least a first target in the first user selection and one or more alarm criteria. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 12 and 27 recite the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 13 and 28 recite in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target. The limitations only recite additional elements recited at a high level of generality. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 14 and 29 recite associating the user with a competitor of the user selection and in which presenting the analysis result comprises presenting the first analysis result in relation to the user selection and the competitor. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., associating, presenting) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
The claims 15 and 30 recite receiving a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result. The limitations only recite additional elements at a high level of generality. These limitations are recited at a high-level of generality (i.e., receiving, re-price) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The additional elements, individually and in combination, also do not amount to significantly more than the abstract idea.
Double Patenting
The non-statutory 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 non-statutory double patenting rejection is appropriate where the claims at issue 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); and 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 a non-statutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-30 rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 12,346,946, claims 1-17 of U.S. Patent No. 11,922,475, and claims 1-17 of U.S. Patent No. 11,514,496 in view of claims being not patentably distinct from each other because claims 1-30 of the instant application substantially recite the limitations of claims 1-15 of U.S. Patent No. 12,346,946, claims 1-17 of U.S. Patent No. 11,922,475, and claims 1-17 of U.S. Patent No. 11,514,496 which is method for summarization and personalization of big data.
The subject matter claimed in the instant application is fully disclosed in the referenced patent and the instant application are claiming common subject matter, as follows in Table 1 and Table 2 below.
Instant Application
Claims 1 & 16. A system comprising a computer processor and a computer
memory, the computer memory comprising instructions which, when executed, cause the system to perform operations, in which the operations include: receiving, via a user computer, over a network, a first user selection including a product, and a brand, vendor and category associated with the product; accessing a set of product information that includes information regarding the selected
product, the set of product information including a set of products, wherein the product information
includes for each product in the set: one or more brands under which the product is sold, a set of
vendors offering it for sale, and a product category;
generating a set of analysis results based on the obtained product information; identifying a first statistical pattern in a first analysis result from the set of analysis results
for the selected product by performing statistical analysis on the product information and the
analysis results,
in which the first statistical pattern is a statistical pattern between two or more types of data
included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes:
a social metric, an identification of which product in a sub-set of products leads or
follows other products in the sub-set of products in terms of price changes, a demand metric based
at least in part on visitors record generated from webpage traffic to one or more online stores at
which the product is available, and in which the demand metric is stored in the database coupled to
the computer, and a reach of the product in terms of the number of people who visit an online sales
venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product, and in which the social metric is stored in a database coupled to the
computer; transmitting to the user computer, over the network, for display to the user, the first analysis
result and the first statistical pattern;
receiving, via the user computer, over the network, a create alert command for the product,
the create alert command including: alert criteria, including at least one of: absolute or percentage change in price, initiation or termination of sales at a venue, and a notification window and frequency; in response to the command, executing the alert and transmit to the user computer, over the network, a notification;
receiving a second user selection and a second analysis result with respect to the second user
selection; and identifying a second statistical pattern in the second analysis result.
Claims 2 & 17. The system of claim 1, in which the first user selection further comprises at least one of a user list and a user favorite.
Claims 3 & 18. The system of claim 2, in which the user list comprises
a custom list or a smart list.
Claims 4 & 19. The system of claim 3, in which the smart list is created
upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product
information and at least one criterion for limiting the first analysis result presented in relation to the
user list, and in which the custom list comprises a list of products provided by the user.
Claims 5 & 20. The system of claim 1, in which the
operations further include:
comparing the second analysis result relating to the second user selection to the first analysis
result, and making a first recommendation to the user based on the comparison of the first and second analysis results.
Claims 6 & 21. The system of claim 5, in which: the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a
promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of:
a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the
product sold by the first vendor or the product sold by the second vendor, and
a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor.
Claims 7 & 22. The system of claim 6 further including:
determining if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommending to the user that the product sold by the first vendor or the product sold by the second vendor be removed from
inventory.
Claims 8 & 23. The system of claim 6, further including: when:
the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and
recommending that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price.
Claims 9 & 24. The system of claim 1, further including: receiving from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identifying the two or more products as substitutes for each other.
Claims 10 & 25. The system of claim 1, further including: receiving an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting.
Claims 11 & 26. The system of claim 10, in which the user-specified
alarm setting comprises at least a first target in the first user selection and one or more alarm criteria.
Claims 12 & 27. The system of claim 11, in which the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target.
Claims 13 & 28. The system of claim 11,
in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and
in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target.
Claims 14 & 29. The system of claim 1, in which the operations further include: associating the user with a competitor of the user selection and in which presenting the
analysis result comprises presenting the first analysis result in relation to the user selection and the
competitor.
Claims 15 and 30. The system of claim 1, in which the operations further include: receiving a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and
in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result.
Patent U.S. 12,346,946
Claim 1. A method including: receiving, via a user computer, over a network, a first user selection including a product, and a brand, vendor and category associated with the product; accessing a set of product information that includes information regarding the selected product, the set of product information including a set of products, wherein the product information includes for each product in the set: one or more brands under which the product is sold, a set of vendors offering it for sale, and a product category; generating a set of analysis results based on the obtained product information; identifying a first statistical pattern in a first analysis result from the set of analysis results for the selected product by performing statistical analysis on the product information and the analysis results, in which the first statistical pattern is a statistical pattern between two or more types of data included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes: a social metric, an identification of which product in a sub-set of products leads or follows other products in the sub-set of products in terms of price changes, a demand metric based at least in part on visitors record generated from webpage traffic to one or more online stores at which the product is available, and in which the demand metric is stored in the database coupled to the computer, and a reach of the product in terms of the number of people who visit an online sales venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product, and in which the social metric is stored in a database coupled to the computer; transmitting to the user computer, over the network, for display to the user, the first analysis result and the first statistical pattern; receiving, via the user computer, over the network, a create alert command for the product, the create alert command including: alert criteria, including at least one of: absolute or percentage change in price, initiation or termination of sales at a venue, and a notification window and frequency; in response to the command, executing the alert and transmit to the user computer, over the network, a notification; receiving a second user selection and a second analysis result with respect to the second user selection; and identifying a second statistical pattern in the second analysis result.
Claim 2. The method of claim 1, in which the first user selection further comprises at least one of a user list and a user favorite.
Claim 3. The method of claim 2, in which the user list comprises a custom list or a smart list.
Claim 4. The method of claim 3, in which the smart list is created upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product information and at least one criterion for limiting the first analysis result presented in relation to the user list, and in which the custom list comprises a list of products provided by the user.
Claim 5. The method of claim 1, further including: comparing the second analysis result relating to the second user selection to the first analysis result, and making a first recommendation to the user based on the comparison of the first and second analysis results.
Claim 6. The method of claim 5, in which: the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of: a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the product sold by the first vendor or the product sold by the second vendor, and a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor.
Claim 7. The method of claim 6 further including: determining if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommending to the user that the product sold by the first vendor or the product sold by the second vendor be removed from inventory.
Claim 8. The method of claim 6, further including: when: the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and recommending that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price.
Claim 9. The method of claim 1, further including: receiving from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identifying the two or more products as substitutes for each other.
Claim 10. The method of claim 1, further including: receiving an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting.
Claim 11. The system method of claim 10, in which the user-specified alarm setting comprises at least a first target in the first user selection and one or more alarm criteria.
Claim 12. The method of claim 11, in which the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target.
Claim 13. The method of claim 11, in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target.
Claim 14. The method of claim 1, further including: associating the user with a competitor of the user selection and in which presenting the analysis result comprises presenting the first analysis result in relation to the user selection and the competitor.
Claim 15. The method of claim 1, further including: receiving a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result.
Patent U.S. 11,922,475
Claims 1 & 17. A method including: receiving, via a user computer, over a network, a first user selection including a product, and a brand, vendor and category associated with the product; accessing a set of product information that includes information regarding the selected product, the set of product information including a set of products, wherein the product information is obtained, at least in part, by one or more crawl agents and wherein the product information includes for each product in the set: one or more brands under which the product is sold, a set of vendors offering it for sale, and a product category; generating a set of analysis results based on the obtained product information; identifying a first statistical pattern in a first analysis result from the set of analysis results for the selected product by performing statistical analysis on the product information and the analysis results, in which the first statistical pattern is a statistical pattern between two or more types of data included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes: a social metric, an identification of which product in a sub-set of products leads or follows other products in the sub-set of products in terms of price changes, a demand metric obtained by at least a crawl agent based at least in part on visitors record generated from webpage traffic to one or more online stores at which the product is available, and in which the demand metric is stored in the database coupled to the computer, and a reach of the product in terms of the number of people who visit an online sales venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product that are obtained periodically by at least the one or more crawl agents to collect from one or more social media websites with which the product has an account, and in which the social metric is stored in a database coupled to the computer; transmitting to the user computer, over the network, for display to the user, the first analysis result and the first statistical pattern; receiving, via the user computer, over the network, a create alert command for the product, the create alert command including: alert criteria, including at least one of: absolute or percentage change in price, initiation or termination of sales at a venue, and a notification window and frequency; in response to the command, executing the alert and transmit to the user computer, over the network, a notification; receiving a second user selection and a second analysis result with respect to the second user selection; identifying a second statistical pattern in the second analysis result; identifying a third statistical pattern between the first statistical pattern and the second statistical pattern; and displaying at least the third statistical pattern, via the user interface, to the user, in which: the first analysis result comprises a price history of the product, the first statistical pattern comprises a cyclic change in the price history of the product, the second analysis result comprises a social metric for the product, the second statistical pattern comprises a cyclic change in the social metric for the product, and the third statistical pattern comprises a cyclic relationship between the first and second statistical patterns.
Claim 2. The method of claim 1, in which the first user selection further comprises at least one of a user list and a user favorite.
Claim 3. The method of claim 2, in which the user list comprises a custom list or a smart list.
Claim 4. The method of claim 3, in which the smart list is created upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product information and at least one criterion for limiting the first analysis result presented in relation to the user list, and in which the custom list comprises a list of products provided by the user.
Claim 6. The method of claim 1, further including: comparing the second analysis result relating to the second user selection to the first analysis result, and making a first recommendation to the user based on the comparison of the first and second analysis results.
Claim 7. The method of claim 6, in which: the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of: a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the product sold by the first vendor or the product sold by the second vendor, and a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor.
Claim 8. The method of claim 7 further including: determining if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommending to the user that the product sold by the first vendor or the product sold by the second vendor be removed from inventory.
Claim 9. The method of claim 7 further including: when: the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and recommending that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price.
Claim 10. The method of claim 1 further including: receiving from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identifying the two or more products as substitutes for each other.
Claim 11. The method of claim 1, further including: receiving an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting.
Claim 12. The method of claim 11, in which the user-specified alarm setting comprises at least a first target in the first user selection and one or more alarm criteria.
Claim 13. The method of claim 12, in which the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target.
Claim 14. The method of claim 12, in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target.
Claim 15. The method of claim 1, further including: associating the user with a competitor of the user selection and in which presenting the analysis result comprises presenting the first analysis result in relation to the user selection and the competitor.
Claim 16. The method of claim 1, further including: receiving a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result.
Table 1
Instant Application
Claims 1 & 16. A system comprising a computer processor and a computer
memory, the computer memory comprising instructions which, when executed, cause the system to perform operations, in which the operations include: receiving, via a user computer, over a network, a first user selection including a product, and a brand, vendor and category associated with the product; accessing a set of product information that includes information regarding the selected
product, the set of product information including a set of products, wherein the product information
includes for each product in the set: one or more brands under which the product is sold, a set of
vendors offering it for sale, and a product category;
generating a set of analysis results based on the obtained product information; identifying a first statistical pattern in a first analysis result from the set of analysis results
for the selected product by performing statistical analysis on the product information and the
analysis results,
in which the first statistical pattern is a statistical pattern between two or more types of data
included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes:
a social metric, an identification of which product in a sub-set of products leads or
follows other products in the sub-set of products in terms of price changes, a demand metric based
at least in part on visitors record generated from webpage traffic to one or more online stores at
which the product is available, and in which the demand metric is stored in the database coupled to
the computer, and a reach of the product in terms of the number of people who visit an online sales
venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product, and in which the social metric is stored in a database coupled to the
computer; transmitting to the user computer, over the network, for display to the user, the first analysis
result and the first statistical pattern;
receiving, via the user computer, over the network, a create alert command for the product,
the create alert command including: alert criteria, including at least one of: absolute or percentage change in price, initiation or termination of sales at a venue, and a notification window and frequency; in response to the command, executing the alert and transmit to the user computer, over the network, a notification;
receiving a second user selection and a second analysis result with respect to the second user
selection; and identifying a second statistical pattern in the second analysis result.
Claims 2 & 17. The system of claim 1, in which the first user selection further comprises at least one of a user list and a user favorite.
Claims 3 & 18. The system of claim 2, in which the user list comprises
a custom list or a smart list.
Claims 4 & 19. The system of claim 3, in which the smart list is created
upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product
information and at least one criterion for limiting the first analysis result presented in relation to the
user list, and in which the custom list comprises a list of products provided by the user.
Claims 5 & 20. The system of claim 1, in which the
operations further include:
comparing the second analysis result relating to the second user selection to the first analysis
result, and making a first recommendation to the user based on the comparison of the first and second analysis results.
Claims 6 & 21. The system of claim 5, in which: the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a
promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of:
a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the
product sold by the first vendor or the product sold by the second vendor, and
a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor.
Claims 7 & 22. The system of claim 6 further including:
determining if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommending to the user that the product sold by the first vendor or the product sold by the second vendor be removed from
inventory.
Claims 8 & 23. The system of claim 6, further including: when:
the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommending an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and
recommending that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price.
Claims 9 & 24. The system of claim 1, further including: receiving from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identifying the two or more products as substitutes for each other.
Claims 10 & 25. The system of claim 1, further including: receiving an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting.
Claims 11 & 26. The system of claim 10, in which the user-specified
alarm setting comprises at least a first target in the first user selection and one or more alarm criteria.
Claims 12 & 27. The system of claim 11, in which the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target.
Claims 13 & 28. The system of claim 11,
in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and
in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target.
Claims 14 & 29. The system of claim 1, in which the operations further include: associating the user with a competitor of the user selection and in which presenting the
analysis result comprises presenting the first analysis result in relation to the user selection and the
competitor.
Claims 15 and 30. The system of claim 1, in which the operations further include: receiving a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and
in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result.
Patent U.S. 11,514,496
Claims 1 & 17. One or more non-transitory computer-readable storage media comprising a plurality of instructions that in response to being executed cause a computer to: receive, via a user computer, over a network, a first user selection including a product, and a brand, vendor and category associated with the product; access a set of product information that includes information regarding the selected product, the set of product information including a set of products, wherein the product information is obtained, at least in part, by one or more crawl agents and wherein the product information includes for each product in the set: one or more brands under which the product is sold, a set of vendors offering it for sale, and a product category; generate a set of analysis results based on the obtained product information; identify a first statistical pattern in a first analysis result from the set of analysis results for the selected product by performing statistical analysis on the product information and the analysis results, in which the first statistical pattern is a statistical pattern between two or more types of data included in the first analysis result or in the product information and in which the two or more types of data share a common aspect, and in which the first statistical pattern comprises a cyclic change in the first analysis result, in which the set of analysis results includes: a social metric, an identification of which product in a sub-set of products leads or follows other products in the sub-set of products in terms of price changes, a demand metric obtained by at least a crawl agent based at least in part on visitors record generated from webpage traffic to one or more online stores at which the product is available, and in which the demand metric is stored in the database coupled to the computer, and a reach of the product in terms of the number of people who visit an online sales venue of the product, in which the social metric is generated based on a number of followers or a number of likes of the product that are obtained periodically by at least the one or more crawl agents to collect from one or more social media websites with which the product has an account, and in which the social metric is stored in a database coupled to the computer; transmit to the user computer, over the network, for display to the user, the first analysis result and the first statistical pattern; receive, via the user computer, over the network, a create alert command for the product, the create alert command including: alert criteria, including at least one of: absolute or percentage change in price, initiation or termination of sales at a venue, and a notification window and frequency; in response to the command, execute the alert and transmit to the user computer, over the network, a notification; receive a second user selection and a second analysis result with respect to the second user selection; identify a second statistical pattern in the second analysis result; identify a third statistical pattern between the first statistical pattern and the second statistical pattern; and display at least the third statistical pattern, via the user interface, to the user, in which: the first analysis result comprises a price history of the product, the first statistical pattern comprises a cyclic change in the price history of the product, the second analysis result comprises a social metric for the product, the second statistical pattern comprises a cyclic change in the social metric for the product, and the third statistical pattern comprises a cyclic relationship between the first and second statistical patterns.
Claim 2. The one or more non-transitory computer-readable storage media of claim 1, in which the first user selection further comprises at least one of a user list and a user favorite.
Claim 3. The one or more non-transitory computer-readable storage media of claim 2, in which the user list comprises a custom list or a smart list.
Claim 4. The one or more non-transitory computer-readable storage media of claim 3, in which the smart list is created upon receipt of a selection of at least one of a brand, a vendor or a category in the set of product information and at least one criterion for limiting the first analysis result presented in relation to the user list, and in which the custom list comprises a list of products provided by the user.
Claim 6. The one or more non-transitory computer-readable storage media of claim 1, further comprising code that when executed causes the computer to: compare the second analysis result relating to the second user selection to the first analysis result, and make a first recommendation to the user based on the comparison of the first and second analysis results.
Claim 7. The one or more non-transitory computer-readable storage media of claim 6, in which: the first analysis result comprises, for a product sold by a first vendor: a demand metric for the product sold by the first vendor, a price history for the product sold by the first vendor, and a promotion metric for the product sold by the first vendor; the second analysis result comprises, for a product sold by a second vendor, a demand metric for the product sold by the second vendor, a price history for the product sold by the second vendor, and a promotion metric for the product sold by the first vendor; and in which the first recommendation comprises at least one of: a recommendation to add or remove the product sold by the first vendor or the product sold by the second vendor from an inventory of the first or second vendor, a recommendation to the first or second vendor to charge a higher or lower price for the product sold by the first vendor or the product sold by the second vendor, and a recommendation to the first or second vendor to increase or decrease a promotion of the product sold by the first vendor or the product sold by the second vendor.
Claim 8. The one or more non-transitory computer-readable storage media of claim 7 further comprising code that when executed causes the computer to: determine if the demand metrics in the first and second analysis results are low; and in response to a determination that they are low, recommend to the user that the product sold by the first vendor or the product sold by the second vendor be removed from inventory.
Claim 9. The one or more non-transitory computer-readable storage media of claim 7, further comprising code that when executed causes the computer to: when: the price histories of the product sold by the first and second vendors indicate a price difference that exceeds a pre-defined threshold, and there is a difference in the promotion metrics between the product sold by the first and second vendors, at least one of: recommend an increase in the price of the product sold by the first vendor or the product sold by the second vendor to a vendor associated with a higher demand metric, a lower promotion metric and a lower current price, recommend an increase in the price of the product sold by the first vendor or the product sold by the second vendor or a lower promotion to a vendor associated with the higher demand metric, a higher promotion metric, and the lower current price, and recommend that the product sold by the first vendor or the product sold by the second vendor be discontinued by a vendor associated with a lower demand metric, the lower promotion metric, and the lower current price.
Claim 10. The one or more non-transitory computer-readable storage media of claim 1, further comprising code that when executed causes the computer to: receive from the user, over the network, an instruction to link two or more different products in the set of product information; and in response to a number of times the two or more different products in the set of product information are linked by any user exceeding a threshold, identify the two or more products as substitutes for each other.
Claim 11. The one or more non-transitory computer-readable storage media of claim 1, further comprising code that when executed causes the computer to: receive an instruction to send a notice to the user when the first analysis result corresponds to a user-specified alarm setting.
Claim 12. The one or more non-transitory computer-readable storage media of claim 11, in which the user-specified alarm setting comprises at least a first target in the first user selection and one or more alarm criteria.
Claim 13. The one or more non-transitory computer-readable storage media of claim 12, in which the one or more alarm criteria comprise at least one of: an absolute or percentage change in price of the first target, a promotion of the first target, and an inception of availability or discontinuation of availability of the first target.
Claim 14. The one or more non-transitory computer-readable storage media of claim 12, in which the one or more alarm criteria comprise a second target comprising at least one of: a product, a category in a product categorization schema, a brand, and a vendor, and in which the one or more alarm criteria comprise at least one of an absolute or percentage change in price between the first and second targets and a change in the promotion status of one of the first and second targets relative to either the first or the second target.
Claim 15. The one or more non-transitory computer-readable storage media of claim 1, further comprising code that when executed causes the computer to: associate the user with a competitor of the user selection and in which presenting the analysis result comprises presenting the first analysis result in relation to the user selection and the competitor.
Claim 16. The one or more non-transitory computer-readable storage media of claim 1, further comprising code that when executed causes the computer to: receive a re-price command from the user, and, in response, reprice a product offered by the user in response to a condition of the first analysis result, and in which the re-price command comprises at least one of an instruction to re-price the product offered by the user to a price higher or lower than a price of a product in the first analysis result.
Table 2
Although the conflicting claims are not identical, they are not patentably distinct from each other because claims 1-30 of the instant application substantially recite the limitations of claims 1-15 of U.S. Patent No. 12,346,946, claims 1-17 of U.S. Patent No. 11,922,475, and claims 1-17 of U.S. Patent No. 11,514,496 which is the method for summarization and personalization of big data. Therefore, it would have been obvious to one of ordinary skill in the art of incorporating a cyclic change and relationship between statistical patterns at the time the invention was made to incorporate the system for summarization and personalization of big data from the independent claims 1-15 of U.S. Patent No. 12,346,946, claims 1-17 of U.S. Patent No. 11,922,475, and claims 1-17 of U.S. Patent No. 11,514,496.
Conclusion
No art has been found that fairly discloses the claimed subject matter either alone or in combination.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LIN LIN M HTAY whose telephone number is (571)272-7293. The examiner can normally be reached on M-F, 7am-3pm, PST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kavita Stanley can be reached on (571) 272-8352. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/L.L.H/Examiner, Art Unit 2153
/KAVITA STANLEY/Supervisory Patent Examiner, Art Unit 2153
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