DETAILED ACTION
Status of Claims
This communication is a non-final action on the merits in response to the amendments and arguments filed on March 26, 2026. Claims 1, 3-5, 12, and 14-16 were amended. Claims 2 and 13 were canceled. Claims 1, 3-12, and 14-20 are currently pending and have been examined.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on March 26, 2026 has been entered.
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, 3-12, and 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1 and 3-11 are directed to a process. Claims 12, 14-17, and 19 are directed to a machine. Claims 18 and 20 are directed to an article of manufacture. As such, each claim is directed to a statutory category of invention.
Step 2A Prong 1
The examiner has identified independents Claims 1 and 9 as the claims that represent the claimed invention for analysis. Claim 1 is similar to independent Claims 12 and 18, and Claim 9 is similar to independent Claims 19 and 20.
Independent Claim 1 recites the following abstract ideas: “A method for generating reply to a topic in a reading application, comprising: determining a topic to be replied among posted book recommendation topics; wherein the topic to be replied corresponds to at least one book recommendation feature; determining a target recommended book matched with the topic to be replied, and generating book recommendation information of the target recommended book; wherein the book recommendation information contains information matched with at least some of book recommendation features; and generating topic reply information of the topic to be replied based on the target recommended book and the book recommendation information; wherein the determining the target recommended book matched with the topic to be replied comprises: extracting content matched with each feature dimension of a plurality of feature dimensions from topic content of the topic to be replied, and determining a book screen feature under a corresponding feature dimension based on the matched content; determining a book recommendation collection corresponding to each of the book screening features among a plurality of candidate recommended books so as to obtain a plurality of book recommendation collections; and determining a book satisfying a book recommendation requirement among the plurality of book recommendation collections as the target recommended book; wherein the plurality of feature dimensions comprises at least one dimension related to a posting user of the topic to be replied and at least one dimension related to a book recommendation label of the topic to be replied, wherein the generating the book recommendation information of the target recommended book comprises: after determining the target recommended book, performing at least one of: determining a first recommendation topic matched with the target recommended book among posted book recommendation topics, determining target topic content associated with the target recommended book in topic content of the first recommendation topic, extracting a recommendation keyword associated with the book recommendation features of the topic to be replied from the target topic content and generating the book recommendation information based on the recommendation keyword; or obtaining target delivery information of the target recommended book on a corresponding target delivery platform, extracting critical delivery information matched with the book recommendation features of the topic to be replied from the target delivery information, and generating the book recommendation information based on the critical delivery information, wherein the extracting the recommendation keyword associated with the book recommendation features of the topic to be replied comprises: performing word segmentation on the target topic content to obtain at least one initial token; calculating a correlation relationship between each initial token and the book recommendation features; and determining an initial token with a correlation relationship satisfying a requirement as a recommendation keyword, so as to obtain the book recommendation information of the target recommended book.”
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions (i.e., a method for generating reply to a topic in a reading application, comprising: determining a topic to be replied among posted book recommendation topics; wherein the topic to be replied corresponds to at least one book recommendation feature; determining a target recommended book matched with the topic to be replied, and generating book recommendation information of the target recommended book; wherein the book recommendation information contains information matched with at least some of book recommendation features; and generating topic reply information of the topic to be replied based on the target recommended book and the book recommendation information; wherein the determining the target recommended book matched with the topic to be replied comprises: extracting content matched with each feature dimension of a plurality of feature dimensions from topic content of the topic to be replied, and determining a book screen feature under a corresponding feature dimension based on the matched content; determining a book recommendation collection corresponding to each of the book screening features among a plurality of candidate recommended books so as to obtain a plurality of book recommendation collections; and determining a book satisfying a book recommendation requirement among the plurality of book recommendation collections as the target recommended book; wherein the plurality of feature dimensions comprises at least one dimension related to a posting user of the topic to be replied and at least one dimension related to a book recommendation label of the topic to be replied, wherein the generating the book recommendation information of the target recommended book comprises: after determining the target recommended book, performing at least one of: determining a first recommendation topic matched with the target recommended book among posted book recommendation topics, determining target topic content associated with the target recommended book in topic content of the first recommendation topic, extracting a recommendation keyword associated with the book recommendation features of the topic to be replied from the target topic content and generating the book recommendation information based on the recommendation keyword; or obtaining target delivery information of the target recommended book on a corresponding target delivery platform, extracting critical delivery information matched with the book recommendation features of the topic to be replied from the target delivery information, and generating the book recommendation information based on the critical delivery information, wherein the extracting the recommendation keyword associated with the book recommendation features of the topic to be replied comprises: performing word segmentation on the target topic content to obtain at least one initial token; calculating a correlation relationship between each initial token and the book recommendation features; and determining an initial token with a correlation relationship satisfying a requirement as a recommendation keyword, so as to obtain the book recommendation information of the target recommended book), but for the recitation of generic computer components (i.e., automatically generating data, a server comprising a processor, and a database). If a claim limitation, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Independent Claim 9 recites the following abstract ideas: “A reply method comprising: detecting a topic browsing request and determining a target recommendation topic corresponding to the topic browsing request; obtaining topic content of the target recommendation topic; wherein the topic content comprises topic recommendation content and topic reply content, and the topic reply content is the topic reply information generated for the target recommendation topic by performing all the steps of the method according to claim 1; and displaying the topic reply content in a topic reply area of a topic display page.”
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions (i.e., a reply method comprising: detecting a topic browsing request and determining a target recommendation topic corresponding to the topic browsing request; obtaining topic content of the target recommendation topic; wherein the topic content comprises topic recommendation content and topic reply content, and the topic reply content is the topic reply information generated for the target recommendation topic by performing all the steps of the method according to claim 1; and displaying the topic reply content in a topic reply area of a topic display page), but for the recitation of generic computer components (i.e., a client). If a claim limitation, under its broadest reasonable interpretation, relates to managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions, 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.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding 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 (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). In particular, claim 1 recites the additional elements of automatically generating data, a server comprising a processor, and a database (in addition to the computer device, bus, and machine-readable instructions of Claim 12, and the non-transitory CRM of Claim 18), and claim 9 recites the additional elements of a client (in addition to the computer device, processor, memory and bus, and machine-readable instructions of Claim 19, and the non-transitory CRM of Claim 20). The computer hardware is recited at a high level of generality (i.e., generic computers receiving, determining, generating, and displaying information) such that it amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application, since they do not involve improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)), they do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and they do not apply or use the abstract idea in some other meaningful way beyond generally linking its use 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)). Therefore, the claim is directed to an abstract idea without a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. The additional elements of using computer hardware (automatically generating data, a server comprising a processor, and database of claim 1 and client of claim 9 (in addition to the computer device, bus, and machine-readable instructions of Claim 12, the computer device, processor, memory and bus, and machine-readable instructions of Claim 19, and the non-transitory CRM of Claims 18 and 20)) amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claim is not patent-eligible.
Dependent claim 10 recites a “multimedia display area,” and dependent claim 11 recites a “triggering operation.” The additional elements are generic interface elements used to implement the abstract idea, and they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Dependent claims 3-8 and 14-17 do not include any additional elements beyond those identified above. They further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. As such, they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Therefore, dependent claims 3-8, 10-11, and 14-17 are directed to an abstract idea, and do not include additional elements that integrate the abstract idea into a practical application, or that are sufficient to amount to significantly more than the abstract idea. Thus, the aforementioned claims are not patent-eligible.
Allowable Subject Matter
Claims 1, 3-12, and 14-20 would be allowable if rewritten or amended to overcome the rejection under 35 U.S.C. 101 set forth in this Office action.
Yu, in combination with the other references relied upon, teaches a method for automatically generating reply to a topic in a reading application, applied to a server comprising a processor, comprising: determining, by the processor, a topic to be replied among posted book recommendation topics; wherein the topic to be replied corresponds to at least one book recommendation feature; determining, by the processor, a target recommended book matched with the topic to be replied, and automatically generating book recommendation information of the target recommended book; wherein the book recommendation information contains information matched with at least some of book recommendation features; and automatically generating, by the processor, topic reply information of the topic to be replied based on the target recommended book and the book recommendation information; wherein the determining the target recommended book matched with the topic to be replied comprises: determining a book screen feature, determining a book recommendation collection corresponding to each of the book screening features among a plurality of candidate recommended books so as to obtain a plurality of book recommendation collections; and determining a book satisfying a book recommendation requirement among the plurality of book recommendation collections as the target recommended book; wherein the automatically generating the book recommendation information of the target recommended book comprises: after determining the target recommended book, performing at least one of: determining a first recommendation topic matched with the target recommended book among posted book recommendation topics, determining target topic content associated with the target recommended book in topic content of the first recommendation topic, extracting a recommendation keyword associated with the book recommendation features of the topic to be replied from the target topic content and generating the book recommendation information based on the recommendation keyword; or obtaining target delivery information of the target recommended book on a corresponding target delivery platform, extracting critical delivery information matched with the book recommendation features of the topic to be replied from the target delivery information, and generating the book recommendation information based on the critical delivery information.
However, the combination of references does not teach extracting content matched with each feature dimension of a plurality of feature dimensions from topic content of the topic to be replied, and determining a book screen feature under a corresponding feature dimension based on the matched content; wherein the plurality of feature dimensions comprises at least one dimension related to a posting user of the topic to be replied and at least one dimension related to a book recommendation label of the topic to be replied, and wherein the extracting the recommendation keyword associated with the book recommendation features of the topic to be replied comprises: performing word segmentation on the target topic content to obtain at least one initial token; calculating a correlation relationship between each initial token and the book recommendation features; and determining an initial token with a correlation relationship satisfying a requirement as a recommendation keyword, so as to obtain the book recommendation information of the target recommended book.
The closest NPL, “User Preferences to Attributes of Books for Personalized Recommendation,” teaches book recommendations based on user interests, preferences, and other factors. However, it does not teach performing word segmentation on a target topic content to obtain at least one initial token; calculating a correlation relationship between each initial token and the book recommendation features; and determining an initial token with a correlation relationship satisfying a requirement as a recommendation keyword, so as to obtain the book recommendation information of the target recommended book.
Response to Arguments
Applicant’s Argument Regarding 35 USC 112(a) Rejections of Claims 1-20: Independent claims 1 and 12 have been amended.
Examiner’s Response: Applicant’s amendments have been fully considered and they resolve the identified issue. As such, the rejection is withdrawn.
Applicant’s Argument Regarding 35 USC 101 Rejection of Claims 1-20:
(1) Claim 1 is directed to a technical solution, not an abstract idea falling within the “Certain Methods of Organizing Human Activity” grouping. The present application addresses the technical problems of low book recommendation accuracy and inefficient screening in the context of large-scale data inherent in the prior art. All steps of the claimed application are rooted in computer-implemented data processing and algorithmic operations, and do not relate to the management of human activity in the context of interactions involving book recommendation topics. This constitutes a fundamental distinction from the abstract idea identified by the Office.
(2) All technical steps rely on the inherent, unique capabilities of a computer and are not manually performable. Amended claim 1 clearly defines the steps for screening a target recommended book, which include, inter alia: extracting content matching each of a plurality of feature dimensions from the topic content of the topic to be replied to and determining a book screening feature for the corresponding feature dimension based on such matched content, generating a book recommendation collection corresponding to each book screening feature; and selecting, from the plurality of book recommendation collections, the target recommended book. Further, the claimed solution incorporates technical steps including word segmentation, correlation calculation, and recommendation keyword screening, and entails structured analysis of large-scale book data, batch feature matching, logical operations on data collections, semantic analysis of natural language, and other such computer-implemented operations. In practical application scenarios involving a vast corpus of candidate books, these operations cannot be practically manually completed within a reasonable time frame. The claimed application is therefore in no way an "automation of a manual process," nor is it a process that can be "performed with pen and paper"—as the Office asserts.
(3) The technical features are specific (not generic) and collectively embody a substantive inventive concept. Amended claim 1 refines the application's core steps into reproducible, implementable specific technical means, and the combination of these features constitutes an inventive technical solution. The claimed application is not a mere aggregation of generic computer functions known in the prior art; rather, it provides a novel, specific technical solution for the field of book recommendation technology and thus is not directed to an abstract idea.
(4) The technical solution is integrated into a practical application. Through the combination of the aforementioned technical features, the present application achieves two core technical improvements: first, it enhances the accuracy of book recommendations by ensuring the target book matches each feature dimension of the topic to be replied to, thereby resolving the mismatch issue arising from single-feature matching in the prior art; second, it optimizes the efficiency of computer-implemented data processing by reducing invalid server retrievals via collection-based screening and lowering the processor's computational load. These improvements yield tangible technical effects in the field of computer data processing, rather than merely optimizing the abstract idea itself, and thus satisfy the legal requirements for integration into a practical application.
(5) Computer components are inextricably integrated with the technical steps, and are not merely used as generic tools. The computer components recited in claim 1—including the server and processor—are not generalized recitations divorced from the claimed technical steps. Instead, they constitute the necessary technical means for implementing feature extraction, data operations, and natural language processing (NLP). The functions of these components are fully integrated with the technical solution and form a core element in achieving the inventive effects of the present invention. The computer is therefore not merely used as a tool to implement an abstract idea.
Examiner’s Response: Applicant’s arguments have been fully considered but they are not persuasive.
(1) The claims are directed to generating book recommendations in response to posted book recommendation topics, and based on features of the topics, which falls under the Certain Methods of Organizing Human Activity grouping of abstract ideas, and the computer is used as a tool to implement the abstract idea. Further, regarding Applicant’s argument that the present application “addresses the technical problems of low book recommendation accuracy and inefficient screening in the context of large-scale data inherent in the prior art,” the specification does not provide any details of how the claimed invention provides any improvement to the functioning of computer technology.
(2) The steps of extracting content matching each of a plurality of feature dimensions from the topic content of the topic to be replied to and determining a book screening feature for the corresponding feature dimension based on such matched content, generating a book recommendation collection corresponding to each book screening feature, and selecting, from the plurality of book recommendation collections, the target recommended book, are all part of the abstract idea itself, and the implementation of these steps on a computer is a use of the computer as a tool to implement the abstract idea. Regarding Applicant’s argument that “operations cannot be practically manually completed within a reasonable time frame,” and that the “claimed application is therefore in no way an automation of a manual process,” the present claims do not reflect this. However, even if this were not an automation of a manual process, the claims do not provide any improvement to the functioning of the computer itself, and as previously stated, neither does the specification provide any details of how the claimed invention provides any improvement to the functioning of computer technology. Regarding Applicant’s argument that this is not a process than can be performed with pen and paper, the claim was not rejected under Mental Processes, rather, it was rejected under Certain Methods of Organizing Human Activity.
(3) The claim recites only the idea of a solution, and fails to recite details of how a solution to a problem is accomplished.
(4) As previously stated, the claims do not provide any improvement to the functioning of the computer itself, neither does the specification provide any details of how the claimed invention provides any improvement to the functioning of computer technology. The additional elements do not integrate the abstract idea into a practical application.
(5) The implementation of feature extraction, data operations, and NLP using computer components does not provide a technical improvement to the computer. Rather, the computer is being used in its ordinary capacity.
Applicant’s Argument Regarding 35 USC 103 Rejections of Claims 1-20: The claims have been amended, and the applied references do not disclose or render obvious the combination recited in the amended claims.
Examiner’s Response: Applicant’s arguments have been fully considered and are persuasive. The rejection has been withdrawn.
Conclusion
The prior art made of record and not relied upon, considered pertinent to applicant’s disclosure or directed to the state of art, is listed on the enclosed PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARMA EL-CHANTI whose telephone number is (571)272-3404. The examiner can normally be reached T-Sa 10am-6pm ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah Monfeldt can be reached at (571)270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KARMA A EL-CHANTI/Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629
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