DETAILED ACTION
This communication is a Non-Final Office Action on the merits in response to communications received on 01/16/2026. Claim 1 has been canceled. Therefore, claims 2-22 are pending and have been addressed below. 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
1. 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 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 non-statutory 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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The 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/process/file/efs/guidance/eTD-info-I.jsp.
2. Claims 2-22 are rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 12,561,721 (Application No. 17/167,327). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims recite corresponding limitations that are recited in claims 1-15 of U.S. Patent No. 12,561,721.
Claims 1, 8, and 15 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 2, 12, and 22 in other words, claims 2, 12, and 22 are anticipated by claims 1, 8, and 15 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “receive a feedback item pertaining to an entity, wherein the feedback item is received at least in part by performing feedback collection over a network and from one or more source sites, including using a web scraper to scrape a source site based at least in part on a determination that querying of the source site using an Application Programming Interface (API) is unavailable for the source site; receive information pertaining to a plurality of candidate sources of the feedback item; and determine a probabilistic mapping between the feedback item and the plurality of candidate sources of the feedback item, wherein determining the probabilistic mapping comprises determining, for a given candidate source in the plurality of candidate sources, a likelihood that the feedback item is attributed to the given candidate source, wherein the probabilistic mapping is determined at least in part by using a feedback attribution model that is trained using training data that includes a piece of feedback that is known to be attributed to a particular individual, and wherein generating of the piece of feedback that is known to be attributed to the particular individual is facilitated at least in part by transmitting a review request to the particular individual responsive to an interaction involving the particular individual.”
Claims 2 and 9 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 3 and 13 or, in other words, claims 3 and 13 are anticipated by claims 2 and 9 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein the plurality of candidate sources is selected based at least in part on a set of characteristics of the feedback item.”
Claims 3 and 10 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 4 and 14 or, in other words, claims 4 and 14 are anticipated by claims 3 and 10 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein the set of characteristics of the feedback item used to select the plurality of candidate sources comprises at least one of a location of the entity to which the feedback item is directed and a time that the feedback item was left.”
Claims 4 and 11 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 5 and 15 or, in other words, claims 5 and 15 are anticipated by claims 4 and 11 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein the plurality of candidate sources of the feedback item comprises a plurality of individuals, wherein the information pertaining to the plurality of candidate sources comprises information pertaining to the plurality of individuals, and wherein the information pertaining to the plurality of individuals comprises information associated with interaction events between the plurality of individuals and the entity.”
Claims 5 and 12 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 6 and 16 or, in other words, claims 6 and 16 are anticipated by claims 5 and 12 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein the one or more processors are configured to collect the information associated with the interaction events from a Customer Relationship Management (CRM) system”
Claims 6 and 13 of U.S. Patent No. 12,561,721 fall entirely within the scope of claim 7 and 17 or, in other words, claims 7 and 17 are anticipated by claims 6 and 13 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein determining the probabilistic mapping comprises: determining a feedback feature vector comprising a set of features of the feedback item; based at least in part on information pertaining to the given candidate source in the plurality of candidate sources, determining, for the given candidate source, a corresponding candidate source feature vector comprising features associated with the given candidate source; based at least in part on at least one of the feedback feature vector or the candidate source feature vector, determining an attribution feature vector; and determining, based at least in part on the attribution feature vector, the likelihood that the feedback item is attributed to the given candidate source.”
Claims 7 and 14 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 9 and 19 or, in other words, claims 9 and 19 are anticipated by claims 7 and 14 of U.S. Patent No. 12,561,721. Specifically, because both inventions disclose equivalent elements such as: “wherein the feedback item comprises one of a review, a survey, a listing, a social comment, and a search result.”
Claims 1, 8, and 15 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 8 and 18 or, in other words, claims 8 and 18 are anticipated by claims 1, 8, and 15 of U.S. Patent No. 12,561,721.
Specifically, because both inventions disclose equivalent elements such as: “wherein determining the likelihood that the feedback item is attributed to the given candidate source comprises providing the attribution feature vector as input to the feedback attribution model.”
Claims 1, 8, and 15 of U.S. Patent No. 12,561,721 fall entirely within the scope of claims 10 and 20 or, in other words, claims 10 and 20 are anticipated by claims 1, 8, and 15 of U.S. Patent No. 12,561,721.
Specifically, because both inventions disclose equivalent elements such as: “determining, based at least in part on a plurality of determined likelihoods, a measure of likelihood that the feedback item is not attributed to any of candidate sources in the plurality of candidate sources”
Claims 1, 8, and 15 of U.S. Patent No. 12,561,721 fall entirely within the scope of claim 11 and 21 or, in other words, claims 11 and 21 are anticipated by claims 1, 8, and 15 of U.S. Patent No. 12,561,721.
Specifically, because both inventions disclose equivalent elements such as: “generate an alert based at least in part on the measure of likelihood that the feedback item is not attributed to any of the candidate sources in the plurality of candidate sources”
Claim Rejections – 35 USC §101
3. 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.
4. Claims 2-22 are rejected under 35 U.S.C. § 101 because the claimed invention is directed an abstract idea without significantly more.
5. Regarding Step 1, Claim 2 recites a machine (i.e., a "concrete thing, consisting of parts, or of certain devices and combination of devices”), Claim 12 recites a process, (i.e., an act or step, or a series of acts or steps.), Claim 22 recites a manufacture, (i.e., an article that is given a new form, quality, property, or combination through man-made or artificial means.) Thus, each of these claims fall within one of the four statutory categories.
6. Under Step 2A [Prong 1]:
Claims 2, 12, and 22 recite:
“determine a probabilistic mapping between the feedback item and the plurality of candidate sources of the feedback item, wherein determining the probabilistic mapping comprises determining, for a given candidate source in the plurality of candidate sources, a likelihood that the feedback item is attributed to the given candidate source, wherein the probabilistic mapping is determined using training data that includes a piece of feedback that is known to be attributed to a particular individual, and wherein generating of the piece of feedback that is known to be attributed to the particular individual is facilitated at least in part by transmitting a review request to the particular individual responsive to an interaction involving the particular individual.”
The limitations above demonstrate the independent claims recite an abstract idea of probabilistic mapping operations to determine who likely wrote a piece of feedback even when the feedback does not clearly identify the author which encompasses commercial interactions (i.e., advertising, marketing or sales activities, business relations) and mental processes (i.e., observations, evaluations, judgements, opinions) and covers concepts that fall within the certain methods of organizing human activity and mental process groupings of abstract ideas. See MPEP 2106.04 II
The Applicant’s Specification emphasizes in at least [0002] Businesses are increasingly concerned with their online reputations. As more review websites are created, and as more users post more content to those sites, it is becoming increasingly difficult for businesses to monitor such sites. Further, it can be difficult for businesses to determine whether they need to, and how they can, improve their online reputations.
Consistent with the disclosure, the limitations in the context of the claim fall within the certain methods of organizing human activity grouping because the steps perform probabilistic mapping operations to determine who likely wrote a piece of feedback even when the feedback does not clearly identify the author which pertains to marketing/sales activities or business relations that companies/businesses perform to manage their reputation. Also, the series of steps describe mental processes for determining a probabilistic mapping because the acts carry out comparisons and/or evaluations relating to the feedback provided within user-authored reviews to identify who authored the review. If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping. As such, the claim recites an abstract idea.
7. Regarding Step 2A [Prong 2], independent claims recite the following additional elements which do not amount to a practical application:
“a system”, “a memory”, “one or more processors”, “over a network”, “from one or more source sites”, “using a web scraper”, “a source site”, “using an Application Programming Interface (API) is unavailable for the source site”, “at least in part by using a feedback attribution model that is trained”, “a computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:” – see claims 2, 12, and 22 are described at a high-level of generality in light of the Specification [¶ 0008, 0013, 0078-0079, 0108-0110].
The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor. In this specification, these implementations, or any other form that the invention may take, may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the invention. Unless stated otherwise, a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task. As used herein, the term ‘processor’ refers to one or more devices, circuits, and/or processing cores configured to process data, such as computer program instructions.
Reputation platform 102 is configured to collect reputation and other online feedback data from a variety of sources, including review websites 108-112, social networking websites 118-120, listing website 122, and other websites 124-126.
In some embodiments, the feedback collection is configured to collect feedback data by performing scraping. For example, in some cases, the approaches such as those described above for collecting feedback data may not be available. For example, a source site may not have the capability to provide real-time updates. As another example, polling may not be available for a source site because, for example, the functionality is not supported, or because there are no credentials available because the location changed their social network account password, such that the platform is no longer able to collect feedback data from the source site. As another example, some source sites do not provide interfaces such as APIs by which to query for and collect feedback data. In such cases, helpers such as web scrapers may be used to scrape feedback data from a source site. The scraping may be performed on a periodic basis (e.g., every 24 hours). The web scrapers may also be used to collect feedback data from sites where platform 102 does not have the ability to obtain credentials. For example, some source sites do not provide their API for reviews.
Since the additional elements recited in the claim are described in general terms, devoid any particulars, the additional elements may be broadly but reasonably construed as generic computing components being used to implement the abstract idea on a computer. As such, the additional elements are merely adding the words “apply it” with the judicial exception, or mere instructions to implement the abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05 (f)
The other additional elements of: “receive a feedback item pertaining to an entity, wherein the feedback item is received at least in part by performing feedback collection, including…to scrape…based at least in part on a determination that querying…;”, “receive information pertaining to a plurality of candidate sources of the feedback item;” simply add insignificant extra-solution activity, [i.e., data collection/data gathering], to the judicial exception, as discussed in MPEP 2106.05(g).
Thus, the additional claim elements are not indicative of integration into a practical application, because the claims do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea and the claims are directed to an abstract idea.
6. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of: “a system”, “a memory”, “one or more processors”, “over a network”, “from one or more source sites”, “using a web scraper”, “a source site”, “using an Application Programming Interface (API) is unavailable for the source site”, “at least in part by using a feedback attribution model that is trained”, “a computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:” – see claims 2, 12, and 22 are at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept.
The other additional elements of: “receive a feedback item pertaining to an entity, wherein the feedback item is received at least in part by performing feedback collection, including…to scrape…based at least in part on a determination that querying…;”,“receive information pertaining to a plurality of candidate sources of the feedback item;” were considered to be insignificant extra-solution activity under Step 2A Prong Two, and thus must be re-evaluated in Step 2B to determine whether they are well-understood, routine, conventional activity in the field.
According to Symantec, TLI Communications, OIP Techs, Versata Dev. Group court decisions cited in MPEP 2106.05(d)(II) indicate: “receiving or transmitting data over a network” and “storing and retrieving information in memory” is/are well-understood, routine, conventional activity. Thus, at Step 2B the claim(s) are ineligible.
7. Dependent claims 3-11 and 13-21 are addressed below:
claims 3 and 13 recite “wherein the plurality of candidate sources is selected based at least in part on a set of characteristics of the feedback item” further describes the information/data recited within the abstract idea but does not make the claim any less abstract, claims 4 and 14 recite “wherein the set of characteristics of the feedback item used to select the plurality of candidate sources comprises at least one of a location of the entity to which the feedback item is directed and a time that the feedback item was left.” further describes the information/data recited within the abstract idea but does not make the claim any less abstract, claims 5 and 15 recite “wherein the plurality of candidate sources of the feedback item comprises a plurality of individuals, wherein the information pertaining to the plurality of candidate sources comprises information pertaining to the plurality of individuals, and wherein the information pertaining to the plurality of individuals comprises information associated with interaction events between the plurality of individuals and the entity” further describes the information/data recited within the abstract idea but does not make the claim any less abstract, claims 6 and 16 recite “wherein the one or more processors are configured to collect the information associated with the interaction events from a Customer Relationship Management (CRM) system.” adds insignificant extra-solution activity, [i.e., data collection/ data gathering], to the judicial exception, as discussed in MPEP 2106.05(g). Here, the additional elements of “one or more processors” and “a Customer Relationship Management (CRM) system” operate in their ordinary capacity for retrieving or storing information, as discussed in MPEP 2106.05(f), claims 7 and 17 recite “wherein determining the probabilistic mapping comprises: determining a feedback feature vector comprising a set of features of the feedback item; based at least in part on information pertaining to the given candidate source in the plurality of candidate sources, determining, for the given candidate source, a corresponding candidate source feature vector comprising features associated with the given candidate source; based at least in part on at least one of the feedback feature vector or the candidate source feature vector, determining an attribution feature vector; and determining, based at least in part on the attribution feature vector, the likelihood that the feedback item is attributed to the given candidate source” further narrows or specifies how the abstract idea is being performed but does not make the claim any less abstract, claims 8 and 18 recite “wherein determining the likelihood that the feedback item is attributed to the given candidate source comprises providing the attribution feature vector as input to the feedback attribution model” further narrows or specifies how the abstract idea is being performed but does not make the claim any less abstract. Here, the additional element of “feedback attribution model” operates in its ordinary capacity for receiving input, as discussed in MPEP 2106.05(f), claims 9 and 19 recite “wherein the feedback item comprises one of a review, a survey, a listing, a social comment, and a search result” further describes the data or information recited within the abstract idea, but does not make the claim any less abstract, claims 10 and 20 recite “determining, based at least in part on a plurality of determined likelihoods, a measure of likelihood that the feedback item is not attributed to any of candidate sources in the plurality of candidate sources” further narrows or specifies how the abstract idea is being performed but does not make the claim any less abstract, claims 11 and 21 recite “generate an alert based at least in part on the measure of likelihood that the feedback item is not attributed to any of the candidate sources in the plurality of candidate sources” further narrows or specifies how the abstract idea is being performed but does not make the claim any less abstract. Accordingly, the dependent claims fail to impose any meaningful limits on integrating the abstract idea into a practical application. Thus, after considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims are not enough to transform the abstract idea into a patent-eligible invention since the claim limitations do not amount to a practical application or significantly more than an abstract idea.
Allowable Subject Matter
Claims 2-22 would be allowable over the prior art if the double patenting rejection is overcome. The following is a statement of reasons for the indication of allowable subject matter: With respect to 35 USC 103, as in application (17/167,327), the instant case claims recite “receive a feedback item pertaining to an entity, wherein the feedback item is received at least in part by performing feedback collection over a network and from one or more source sites, including using a web scraper to scrape a source site based at least in part on a determination that querying of the source site using an Application Programming Interface (API) is unavailable for the source site; receive information pertaining to a plurality of candidate sources of the feedback item; and determine a probabilistic mapping between the feedback item and the plurality of candidate sources of the feedback item, wherein determining the probabilistic mapping comprises determining, for a given candidate source in the plurality of candidate sources, a likelihood that the feedback item is attributed to the given candidate source, wherein the probabilistic mapping is determined at least in part by using a feedback attribution model that is trained using training data that includes a piece of feedback that is known to be attributed to a particular individual, and wherein generating of the piece of feedback that is known to be attributed to the particular individual is facilitated at least in part by transmitting a review request to the particular individual responsive to an interaction involving the particular individual.”
The most relevant prior art includes the following:
Green (US 2010/0169315 A1) - (abstract, ¶ 0058: An attribution analysis and correlation system can include a content manager and a semantic correlation module. The content manager can receive a list identifying at least one contributor to be evaluated. The content manager can also mine at least one community for content pertaining to the contributor(s). The semantic correlation module can generate correlation results by performing a semantic analysis and correlation on the persistent content and attributions corresponding to the contributor(s).)
Scholtes (US2014/0222928 A1) – (¶ 0054: System and process of training, testing and employing a machine learning model from an authorship support vector machine (SVM) to recognize authors based on extracted features from documents. In FIG. 8, for each document 801, a set of characteristics is derived from which feature vectors 802 are derived. The feature vectors 802 are used to train one machine learning model for each known candidate author by using a machine learning algorithm 805, for example, a Support Vector Machine (SVM). After testing and evaluating the quality of the machine learning model, as further explained, the derived machine learning model can be used to classify documents from a text 803 with an unknown author by deriving characteristics from the document and converting them into a feature vector 804 in a similar manner as employed during the training of the machine learning model. The feature vector 804 is then matched against each machine learning model derived for each of the candidate authors, and a prediction as to whether or not the document has been written by the author corresponding to the machine learning model is made in step 806. Step 806 returns a confidence value, for example, indicating 0 for no match, 1 for a perfect match, and any suitable value in between indicating the probability for a match. By using a suitable threshold, potential candidate authors can be determined in order of decreasing probability and can be presented as a ranked list for each of the documents in step 807.)
None of the evidence at hand teaches or suggests the combination of underlined features, nor does there exist an appropriate rationale for further modification of the evidence at hand. It is hereby asserted by the Examiner that, in light of the above and in further deliberation over all the evidence at hand, that the claims include allowable subject matter as the evidence at hand does not anticipate the claims and does not render obvious any further modification of the references to a person of ordinary skill in the art.
The following non-patent literature is cited to show the best non-patent literature prior art found including:
M. Rosen-Zvi, T. Griffiths, M. Steyvers, P. Smyth, “The Author-Topic Model for Authors and Documents”, July 2012, pgs. 1-8, downloaded from: https://doi.org/10.48550/arXiv.1207.4169
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EHRIN PRATT whose telephone number is (571)270-3184. The examiner can normally be reached 8-5 EST Monday-Friday.
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/EHRIN L PRATT/Examiner, Art Unit 3629
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629
