DETAILED ACTION
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 .
Status of Claims
This action is in reply to the communications filed on 9/4/2025.
Claims 1-4 are currently pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/24/2025, 9/4/2025 are being considered by the examiner.
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 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the Subject Matter Eligibility Test for Products and Processes, the claims must be directed to one of the four statutory categories. All the claims are directed to one of the four statutory categories (NO). Claims 1-4 are directed to a non-transitory computer-readable medium (the “information processing device” recites no hardware, only functionality, and is being interpreted as software per se, see below).
Under Step 2A of the Subject Matter Eligibility Test for Products and Processes (see MPEP § 2106 Subsection III), it is determined whether the claims are directed to a judicially recognized exception. Step 2A is a two-prong inquiry.
Under Prong 1, it is determined whether the claim recites a judicial exception (YES). Taking Claim 1 as representative, the claim recites limitations that fall within the certain methods of organizing human activity grouping of abstract ideas, including:
An information processing device comprising:
a style selection unit that selects style information of a user based on user information including at least one of attribute information and behavior information of the user;
a description generation unit that generates a recommendation description based on a predetermined recommendation basis for recommended content and the style information of the user selected by the style selection unit; and
a presentation unit that presents the recommendation description generated by the description generation unit to the user.
Certain methods of organizing human activity include:
fundamental economic principles or practices (including hedging, insurance, and mitigating risk)
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; and business relations)
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)
The limitations as emphasized, are a process that, under its broadest reasonable interpretation, covers a commercial interaction. That is, other than reciting that a user interface is generated from the list and products are displayed on the user interface, nothing in the claim element precludes the step from practically being performed by people. For example, “selects, generates, and presents” in the context of this claim encompasses advertising, and marketing or sales activities.
If a claim limitation, under its broadest reasonable interpretation, covers a commercial interaction but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Under Prong 2, it is determined whether the claim recites additional elements that integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application (NO).
The claim recites additional elements beyond the judicial exception(s), including:
An information processing device comprising:
a style selection unit that selects style information of a user based on user information including at least one of attribute information and behavior information of the user;
a description generation unit that generates a recommendation description based on a predetermined recommendation basis for recommended content and the style information of the user selected by the style selection unit; and
a presentation unit that presents the recommendation description generated by the description generation unit to the user.
These limitations are not indicative of integration into a practical application because:
The additional elements of claim 1 are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than mere instructions to implement or apply the abstract idea on a generic computing hardware (or, merely use a computer as a tool to perform an abstract idea.) Specifically, the additional element of a style selection unit, a description generation unit, and a presentation unit, is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of connecting to a platform on a network) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does 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. Further, the additional elements to no more than generally link the use of the judicial exception to a particular technological environment or field of use (such as computers or computing networks). For example, stating that the recommendation description is generated by a description generation unit, only generally links the commercial interactions and management of relationships or interactions between people to a computer environment. Employing well-known computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not integrate the exception into a practical application.
Additionally, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to i) reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, ii) apply the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, iii) effect a transformation or reduction of a particular article to a different state or thing, or iv) apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, the judicial exception is not integrated into a practical application.
Under Step 2B, it is determined whether the claims recite additional elements that amount to significantly more than the judicial exception. The claims of the present application do not include additional elements that are sufficient to amount to significantly more than the judicial exception (NO).
In the case of system claim 1, taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept. As discussed above under step 2A (prong 2) with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed functions amount to no more than a general link to a technological environment.
Even considered as an ordered combination (as a whole), the additional elements do not add anything significantly more than when considered individually.
Therefore, claim 1 does not provide an inventive concept and does not qualify as eligible subject matter.
Claims 2-4 are dependencies of claims 1. The dependent claims do not add “significantly more” to the abstract idea. They recite additional functions that describe the abstract idea and only generally link the abstract idea to a particular technological environment, including:
wherein the description generation unit performs learning with the style information and the recommendation description generated based on the recommendation basis, reflecting the recommendation basis, as an explanatory variable, and a recommendation description that takes into account the style information as a target variable, and generates the recommendation description based on learning results obtained through the learning. (no details are recited regarding steps or data involved in the learning, only generally links the abstract idea to a particular technological environment (machine learning))
wherein the style selection unit learns, using a reinforcement learning approach, a probability function as to which style information should be selected for which user based on the user information and behavioral results of the user related to content corresponding to recommendation descriptions linked to previously selected style information, and selects the style information of the user using the probability function obtained through the learning. (only generally links the abstract idea to a technological environment)
wherein the style selection unit learns, using a reinforcement learning approach, the probability function for selecting style information that maximizes a reward related to the user's response to the content when the user information is input, and selects the style information of the user using the probability function obtained through the learning. (only generally links the abstract idea to a technological environment)
Accordingly, the Examiner concludes that there are no meaningful limitations in the claim that transform the judicial exception into a patent eligible application such that the claim amounts to significantly more than the judicial exception itself. The analysis above applies to all statutory categories of invention.
Claim 1-4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed signals per se.
Claim 1-4 is directed to a device. Claims are given their broadest reasonable interpretation consistent with the specification during proceedings before the USPTO. See In re Zletz, 893.2d 319 (Fed. Cir. 1989). The broadest reasonable interpretation of a claim drawn to a device reciting no hardware components and reciting only functionality are interpreted as a computer readable medium which typically covers forms of non-transitory media and transitory propaganda signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See MPEP 2111.01. Signals per se are non-statutory subject matter, therefore claims 1-4 are non-statutory. See In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Cir. 2007) (See Kappos Memo dated January 26, 2010).
Applicant is advised that amending the claims to recite a “non-transitory computer readable medium” shall overcome the noted rejection.
Claim Rejections - 35 USC § 103
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 of this title, 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.
Claims 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over CN 114896497 A to SU (citations refer to attached translation document) in view of US 20200097523 A1 to Sato.
Regarding Claim 1, SU discloses An information processing device comprising:
a style selection unit that selects style information of a user based on user information including at least one of attribute information and behavior information of the user; ([p.3] reinforcement learning method, the real-time interaction of the user and the recommendation list is the current preference of the reward learning user, updating the recommendation list. [p. 9] history interactive data C of the user and the clothing item, each data comprises a user number, a garment single product number and interaction mode)
But does not explicitly disclose a description generation unit that generates a recommendation description based on a predetermined recommendation basis for recommended content and the style information of the user selected by the style selection unit; and a presentation unit that presents the recommendation description generated by the description generation unit to the user.
Sato, on the other hand, teaches a description generation unit that generates a recommendation description based on a predetermined recommendation basis for recommended content and the style information of the user selected by the style selection unit; and a presentation unit that presents the recommendation description generated by the description generation unit to the user. ([0043] selecting a product as a recommendation target displayed on the display unit 23. [0038] The descriptive text creation unit 15 creates a descriptive text describing the product selected by the selection unit 14. In this case, the descriptive text creation unit 15 creates a descriptive text on the basis of the description style selected by the selection unit 14. The descriptive text creation unit 15 transmits the created descriptive text to the user terminal 20 via the transmitting-receiving unit 12.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of SU to include the features as taught by Sato. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify SU in order to raising the probability that the user will select the recommendation target (Sato, [0005]).
Regarding Claim 2, SU in view of Sato teaches the method of claim 1.
Sato teaches wherein the description generation unit performs learning with the style information and the recommendation description generated based on the recommendation basis, reflecting the recommendation basis, as an explanatory variable, and a recommendation description that takes into account the style information as a target variable, and generates the recommendation description based on learning results obtained through the learning.. ([0025] Also, the management server 10 analyzes the history information, performs machine learning to learn the user's preferences regarding the description styles of descriptive text and the compatibility between products and the description styles of descriptive text, and creates a predictive model on the basis of the learning results. Additionally, the created predictive model is used to decide which product to recommend to the user and which description style of descriptive text to describe the recommended product, and creates a descriptive text of the recommended product on the basis of the decided description style.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of SU to include the features as taught by Sato. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify SU in order to raising the probability that the user will select the recommendation target (Sato, [0005]).
Regarding Claim 3, SU in view of Sato teaches the method of claim 1.
SU discloses wherein the style selection unit learns, using a reinforcement learning approach, a probability function as to which style information should be selected for which user based on the user information and behavioral results of the user related to content corresponding to recommendation descriptions linked to previously selected style information, and selects the style information of the user using the probability function obtained through the learning. ([p. 9] the invention further claims a personalized garment recommendation system based on reinforcement learning, [p. 5] a user history preference unit, used for according to the user history interaction data of the clothing item, giving user different interactive mode of the clothing single product with different weights, and the weight as the coefficient, the clothing set in the clothing item of visual compatibility representation vector sum, the preference score of the clothing set as the user; [p. 6] reinforcement learning method, the real-time interaction of the user and the recommendation list is the current preference of the reward learning user, updating the recommendation list.)
Regarding Claim 4, SU in view of Sato teaches the method of claim 1.
SU discloses wherein the style selection unit learns, using a reinforcement learning approach, the probability function for selecting style information that maximizes a reward related to the user's response to the content when the user information is input, and selects the style information of the user using the probability function obtained through the learning.. ([p. 6] primarily recommending that the user recommendation not only satisfy the history clothing preference but also has fashion clothing collocation, it is good for the reinforcement learning preference of the user to obtain the goal of maximizing the reward, and improves the efficiency; [p. 11] in order to ensure the recommendation accuracy of maximum reward at the same time, under the state qt from the clothing single data set selected K clothing item recommended to the user, so that the expected reward is maximum,)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michelle T. Kringen whose telephone number is (571)270-0159. The examiner can normally be reached M-F: 11am-7pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached at (571)272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHELLE T KRINGEN/Primary Examiner, Art Unit 3689
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