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 AIA .
Status of Claims
This communication is a Final Office action in response to communications received on 11/26/2025. Claims 1, 2, 4, 6, 9 and 10 have been amended. Claim 8 has been canceled. Therefore, claims 1-7 and 9-10 are currently pending and have been addressed below.
Response to Amendment
With respect to the title of the invention, Examiner acknowledges an amended title has been received. Examiner withdraws the specification objection.
Applicant has canceled claim 8 and amended claim 9. Examiner withdraws the 112(b) rejections for claims 8-9.
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 1-7 and 9-10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception without a practical application and significantly more.
Step 1: Identifying Statutory Categories
When considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claims are directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (i.e., Step 1). In the instant case, claims 1-7 are directed to an apparatus (i.e. a machine). Claim 9 is directed to a method (i.e. a process). Claim 10 is directed to a non-transitory storage medium (i.e. an article of manufacture). Thus, each of these claims fall within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A: Prong One: Abstract Ideas
Claims 1-7 and 9-10 are rejected under 35 U.S.C. 101 because the claimed invention recites an abstract idea. Independent claim 1, analogous to independent claims 9 and 10 recites: an obtaining process that obtains a first document in which contents of a first business negotiation are described in a natural language; a selection process that refers, for each of multiple second business negotiations that are other than the first business negotiation, a second document in which contents of the second business negotiation are described in a natural language; information on a cluster to which the second document belongs; and a business negotiation condition indicated in a document belonging to the cluster, and selects a cluster from among multiple clusters formed in clustering of the second documents, on the basis of a degree of similarity between the first document and each of at least one or all of the second documents; and an output process that outputs information indicative of a condition of a business negotiation, the information being associated with the cluster selected in the selection process, wherein the first business negotiation is a business negotiation currently in progress, and the second business negotiations are business negotiations the results of which have been confirmed in the past, wherein in the obtaining process, further obtains a third document including contents of the first business negotiation and having a creation time earlier than that of the first document, wherein the second documents are subjected to clustering with reference to each second document and a fourth document including contents of the same second business negotiation as the second document having a creation time earlier than that of the second document, and wherein in the selection process, calculates a degree of similarity between the first document and each second document, on the basis of a degree of similarity between a document set including the first document and the third document, and a document set including the second document and the fourth document. The limitations as drafted, is a process that, under its broadest reasonable interpretation, falls under the abstract groupings of: Mental Processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion (independent claims 1, 9 and 10 recite for example, “obtaining process that obtains a first document in which contents of a first business negotiation are described”; “a selection process that refers, for each of multiple second business negotiations that are other than the first business negotiation, a second document”; “a business negotiation condition indicated in a document”; “selects a cluster from among multiple clusters formed in clustering of the second documents”; “an output process that outputs information indicative of a condition of a business negotiation, the information being associated with the cluster selected in the selection process.”) Concepts performed in the human mind as mental processes because the steps of receiving, determining, generating, storing, detecting, responsive to detecting, updating, and analyzing data mimic human thought processes of observation, evaluation, judgement and opinion, perhaps with paper and pencil, where data interpretation is perceptible in the human mind. See In re TLI Commc’ns LLCPatentLitig., 823 F.3d 607, 611 (Fed. Cir. 2016); FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016)).
Certain methods of organizing human activity (commercial or legal interactions (including advertising, marketing or sales activities or behaviors; business relations; (managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). As the claims discuss sales support and information indicative of a condition of a business negotiation, which is a clear business relations and one of certain methods of organizing human activity. Dependent claims 2-7 add additional limitations, for example: (claim 2) a clustering process that performs clustering on the second documents in accordance with degrees of similarity between documents, to form the multiple clusters; (claim 3) wherein, in the clustering process, clustering on the second documents in accordance with attributes of the second documents; (claim 4) an accepting process that accepts, for each of the multiple clusters, input of the information indicative of a condition of a business negotiation; and an information attaching process that stores the information accepted in the accepting process, in association with information for identifying the cluster; (claim 5) wherein, in the selection process, calculates, as the degree of similarity, a distance in a predetermined feature space between the first document and each of the second documents; (claim 6) wherein in the selection process, selects one or more second documents such that the degree of similarity satisfies a predetermined condition, from among the second documents; and
Step 2A: Prong Two
This judicial exception is not integrated into a practical application because the claims merely describe how to generally “apply” the abstract idea. In particular, the claims only recite the additional elements – (claims 1-7) sales support apparatus, processor(s), a storage device (claim 10) non-transitory storage medium, computer. These additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Simply implementing the abstract idea on generic computer components is not a practical application of the abstract idea, as it adds the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). The limitations generally link the abstract idea to a particular technological environment or field of use (such as computing, see MPEP 2106.05(h)). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception and generally link the abstract idea to a particular technological environment or field of use. Furthermore, claims 1-7 and 9-10 have been fully analyzed to determine whether there are additional elements recited that amount to significantly more than the abstract idea. The limitations fail to include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Thus, nothing in the claim adds significantly more to the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. The claims are ineligible. Therefore, since there are no limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, the claims are rejected under 35 USC 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-7 and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Rowe et al. (US 2022/0261753 A1), hereinafter “Rowe”, over Semenov et al. (US 2022/0156491 A1), hereinafter “Semenov”.
Regarding Claim 1, Rowe teaches A sales support apparatus comprising at least one processor, the at least one processor configured to execute: (Rowe, Figures 1 and 5; Abstract, A software system operates to store information about a plurality of products in a common data management system that serves as a single source of truth for product information… The overall system is a multi-use tool for assortment planning that allows for flexible data sharing across the lifecycle of an item for item definition, budget definition, and vendor negotiation.);
an obtaining process that obtains a first document in which contents of a first business negotiation are described in a natural language; (See at least Rowe, para 0002-0003, negotiations are often accomplished by way of exchanging various spreadsheets (Examiner notes spreadsheets are documents); See Rowe, Figures 7-8, negotiations described in a natural language (English));
a selection process that refers, for each of multiple second business negotiations that are other than the first business negotiation, to a storage device storing: a second document in which contents of the second business negotiation are described in a natural language; …; and a business negotiation condition indicated in a document …, (Rowe, para 0002, teaches business negotiation conditions including multiple different attribute values of the product are negotiated including things such as where the product will be manufactured, what port the product will be shipping from, the number of items in the product, the dimensions of the product, the colors of the product, what the product will be made from, the cost associated with shipping the product, the per item cost of the product and so forth; Rowe, teaches selecting throughout, see at least para 0027, selected item records from the common item data management system. The product negotiation tool mediates the negotiation over product/item sales between buyers and vendors. …. A first subset of item attributes is viewable by the vendor and a second subset of item attributes selected);
an output process that outputs information indicative of a condition of a business negotiation, the information being associated with the … selected in the selection, (Rowe, Figure 5, teaches an output unit; Rowe, Figures 7-8, shows output information of business negotiation with information (For example “updated” or “action”); wherein the first business negotiation is a business negotiation currently in progress, and the second business negotiations are business negotiations the results of which have been confirmed in the past, (See at least Rowe, para 0002, teaches business negotiation conditions including multiple different attribute values of the product are negotiated including things such as the cost associated with shipping the product, the per item cost of the product and so forth; Rowe, para 0033, teaches a planning tool to assist budget managers or merchandise planners in making financial plans (Examiner notes current negotiations)... Information such as general profit margin, budget, historical costs, and other types of information may be provided via the tool (Examiner notes, historical costs have been confirmed in the past)); wherein in the obtaining process, the at least one processor further obtains a third document including contents of the first business negotiation and having a creation time earlier than that of the first document, ... and a fourth document including contents of the same second business negotiation as the second document having a creation time earlier than that of the second document, and (See at least Rowe, para 0002-0003, negotiations are often accomplished by way of exchanging various spreadsheets (Examiner notes spreadsheets are documents); See Rowe, Figures 7-8, teaching negotiation documents with dates. See for example, Figure 8, teaches Business Partner “Happy Feet’, dated 10/05/21). Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches information on a cluster to which the second document belongs…belonging to the cluster, and selects a cluster from among multiple clusters formed in clustering of the second documents, on the basis of a degree of similarity between the first document and each of at least one or all of the second documents; and … cluster ... wherein the second documents are subjected to clustering with reference to each second document ... wherein in the selection process, the at least one processor calculates a degree of similarity between the first document and each second document, on the basis of a degree of similarity between a document set including the first document and the third document, and a document set including the second document and the fourth document (See at least Semenov, Abstract, teaches clusters of documents and similarity measures between them; Semenov, para 0004, teaches the plurality of clusters of documents; … the similarity function is based on one or more of types calculated attributes of the document selected from the group consisting of GRID type attribute; Semenov, Figure 5; para 0047-0048, teaches document clusterization method comprises second level differential classification of the clusters. The processing device performing method analyzes clusters of documents using a first similarity measure to identify a group of adjacent clusters). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with information on a cluster to which the second document belongs…belonging to the cluster, and selects a cluster from among multiple clusters formed in clustering of the second documents, on the basis of a degree of similarity between the first document and each of at least one or all of the second documents; and … cluster ... wherein the second documents are subjected to clustering with reference to each second document ... wherein in the selection process, the at least one processor calculates a degree of similarity between the first document and each second document, on the basis of a degree of similarity between a document set including the first document and the third document, and a document set including the second document and the fourth document as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract). The Rowe invention now incorporating the Semenov invention, has all the limitations of claim 1.
Regarding Claim 2, Rowe, now incorporating Semenov, teaches The sales support apparatus according to claim 1, wherein the at least one processor is further configured to execute.
Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches a clustering process that performs clustering on the second documents in accordance with degrees of similarity between documents, to form the multiple clusters
(See at least Semenov, Abstract, teaches document clusterization comprising: receiving an input document; determining, by evaluating a document similarity function, a plurality of similarity measures, wherein each similarity measure of the plurality of similarity measures reflects a degree of similarity between the input document and a corresponding cluster of documents of a plurality of clusters of documents, based on the plurality of similarity measures… creating a new cluster of documents; and associating the input document with the new cluster of documents.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with a clustering process that performs clustering on the second documents in accordance with degrees of similarity between documents, to form the multiple clusters as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claim 3, Rowe, now incorporating Semenov, teaches The sales support apparatus according to claim 2.
Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches wherein in the clustering process, the at least one processor performs clustering on the second documents in accordance with attributes of the second documents (See at least Semenov, para 0021, teaches “document cluster” may refer to one or more documents combined in a group based on one or more of document characteristics (attributes); para 0039, teaches document clusterization process by performing determination of the similarity measure that takes into account most relevant document attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with wherein in the clustering process, the at least one processor performs clustering on the second documents in accordance with attributes of the second documents as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claim 4, Rowe, now incorporating Semenov, teaches The sales support apparatus according towherein the at least one processor is furtherconfigured to execute:
an accepting process that accepts, … input of the information indicative of a condition of a business negotiation; and an information attaching process that stores the information accepted (Rowe, para 0002, teaches business negotiation conditions including multiple different attribute values of the product are negotiated including things such as where the product will be manufactured, what port the product will be shipping from, the number of items in the product, the dimensions of the product, the colors of the product, what the product will be made from, the cost associated with shipping the product, the per item cost of the product and so forth; See at least Rowe, para 0073, teaches a mass storage device).
Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches for each of the multiple clusters… identifying the cluster (See at least Semenov, Abstract, teaches document clusterization comprising: receiving an input document; determining, by evaluating a document similarity function, a plurality of similarity measures … associating the input document with the cluster of documents.) It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with for each of the multiple clusters… identifying the cluster as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claim 5, Rowe, now incorporating Semenov, teaches The sales support apparatus according toYet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches calculates, as the degree of similarity, a distance in a predetermined feature space between the first document and each of the second documents (Semenov, para 0047-0048, document clusterization method comprises second level differential classification of the clusters, as illustrated in FIG. 5. The processing device performing method analyzes clusters of documents using a first similarity measure to identify a group of adjacent clusters; Two or more clusters are adjacent to each other if the distance between their centroids is less than a predetermined degree of separation.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with calculates, as the degree of similarity, a distance in a predetermined feature space between the first document and each of the second documents as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claim 6, Rowe, now incorporating Semenov, teaches The sales support apparatus according towherein, in the selection process, the at least one processor:
Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches selects one or more second documents such that the degree of similarity satisfies a predetermined condition, from among the second documents; and selects a cluster to which at least one or all of the one or more selected second documents belong, from among the multiple clusters (Semenov, para 0004, the plurality of clusters of documents; … the similarity function is based on one or more of types calculated attributes of the first document selected from the group consisting of GRID type attribute; para 0047-0048, document clusterization method comprises second level differential classification of the clusters, as illustrated in FIG. 5. The processing device performing method analyzes clusters of documents using a first similarity measure to identify a group of adjacent clusters; Two or more clusters are adjacent to each other if the distance between their centroids is less than a predetermined degree of separation.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with selects one or more second documents such that the degree of similarity satisfies a predetermined condition, from among the second documents, and selects a cluster to which at least one or all of the one or more selected second documents belong, from among the multiple clusters as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claim 7, Rowe, now incorporating Semenov, teaches The sales support apparatus according to
Yet, Rowe does not appear to explicitly teach and in the same field of endeavor Semenov teaches calculates a degree of similarity between the first document and a second document that is representative of each of the multiple clusters and is included in the cluster, and selects a cluster, referring to the calculated degree of similarity (Semenov, para 0004, the plurality of clusters of documents; … the similarity function is based on one or more of types calculated attributes of the first document selected from the group consisting of GRID type attribute; para 0047-0048, document clusterization method comprises second level differential classification of the clusters, as illustrated in FIG. 5. The processing device performing method analyzes clusters of documents using a first similarity measure to identify a group of adjacent clusters.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Rowe with calculates a degree of similarity between the first document and a second document that is representative of each of the multiple clusters and is included in the cluster, and selects a cluster, referring to the calculated degree of similarity as taught by Semenov with the motivation for a computer-implemented method for document clusterization (Semenov, Abstract).
Regarding Claims 9 and 10, the claims are an obvious variant to claim 1 above, and are therefore rejected on the same premise. Rowe further teaches a non-transitory storage medium (See at least Rowe, para 0073, teaches non-transitory data storage for the computing system).
Response to Arguments
Applicants arguments filed on 11/26/2025 have been fully considered but they are not persuasive.
Regarding 35 U.5.C. § 101 rejections: Examiner has updated the 101 rejection in light of the most recent claim amendments and maintains the 101 rejection. Applicant’s arguments have been fully considered but are found unpersuasive.
With respect to Applicant’s remarks that the claims do not recite an abstract idea, Examiner respectfully disagrees. With respect to the abstract idea, the claimed invention falls within at least the abstract groupings of certain methods of organizing human activity and mental processes as explained in the above 101 analysis. With respect to Applicants remarks (remarks, page 11), “the claims improve the computer’s own analytical capability.” Examiner respectfully disagrees. With respect to integration of the abstract idea into a practical application, the computing elements are additional elements to perform the steps and amount to no more than mere instructions to apply the exception using generic computer components. Examiner has reviewed Applicants claims and specification and has found only generic computing elements. Further, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Therefore, Examiner maintains the 101 rejection with respect to these and all depending claims unless otherwise indicated.
Regarding 35 U.S.C. § 103 rejections. With respect to the prior art rejections, Applicants arguments have been fully considered but are found unpersuasive. Examiner has updated the rejections in light of the most recent claim amendments. With respect to Applicant’s remarks (remarks page 12): “Applicant respectfully submits that the cited references, and any combination thereof, fail to teach or suggest all the features of claim 1 and, therefore, claim 1 is patentable for at least these reasons.
For instance, there is no suggestion in either Rowe or Semenov that multiple documents should be treated as a "chronological document set" and that similarities between such sets should be compared. As the Examiner noted, Semenov discloses a document clustering technique. However, Semenov' s technique consistently processes a single input document as the unit of analysis. Unlike claim 1, Semenov contains no teaching or suggestion that multiple documents should be grouped together as a set having chronological context, nor that such a set should be compared with other sets as a unified unit.
Moreover, Rowe fails to remedy the deficient teachings of Semenov.
Therefore, even if Rowe and Semenov were combined, as proposed by the grounds of rejection, similarity calculation between chronological sets, as recited in claim 1, nevertheless still cannot be achieved in view of the cited references, and any combination thereof. ” Examiner respectfully disagrees.
As an initial matter “chronological document set” is not claimed. Applicant’s independent claims 1, 9 and 10, recite: “the first business negotiation and having a creation time earlier than that of the first document, wherein the second documents are subjected to clustering with reference to each second document and a fourth document including contents of the same second business negotiation as the second document having a creation time earlier than that of the second document”. Examiner notes this is not the same as “similarity calculation between chronological sets.” Further, Semenov teaches clusters of documents and similarity measures between them. See at least Semenov, Abstract. Therefore Applicants remarks are found unpersuasive and Examiner has updated and maintains the 103 rejections for all claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REBECCA R NOVAK whose telephone number is (571)272-2524. The examiner can normally be reached Monday - Friday 8:30am - 5:00pm EST.
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/R.R.N./ Examiner, Art Unit 3629
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629