DETAILED ACTION
Status of Claims
This communication is the final action on the merits in response to the amendments and arguments filed on September 30, 2025. Claims 1, 4, 6, 9, 12, 15, and 17-18 were amended. Claims 1-20 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 .
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Independent Claims 1 and 12 recite “storing the topic to be replied and the topic reply information in association in a database,” yet Applicant’s specification fails to disclose storing the topic to be replied or the topic reply information in a database.
Because the original disclosure does not support the identified limitations, one of ordinary skill in the art would not recognize the Applicant as in possession of the claimed invention at the time of filing. Therefore, Claims 1 and 12 are rejected under 35 U.S.C. 112(a). Because Claims 2-11 and 13-20 depend upon Claims 1 and 12, these claims are also rejected under 35 U.S.C. 112(a).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-11 are directed to a process. Claims 12-17 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, and storing the topic to be replied and the topic reply information in association ; 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, and generating the book recommendation information based on the target topic content; 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.”
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, and storing the topic to be replied and the topic reply information in association; 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, and generating the book recommendation information based on the target topic content; 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), but for the recitation of generic computer components (i.e., automatically generating data, a server comprising a processor and a memory, 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 memory, 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 a memory, 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 2-8 and 13-17 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 2-8, 10-11, and 13-17 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.
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, 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 1-6 and 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US-10922340) in view of Lorch (US-20130185198).
Claim 1 (and Similarly Claims 12 and 18)
Yu teaches the following limitations:
A method for automatically generating reply to a topic in a reading application, applied to a server comprising a processor and a memory, 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 (Col. 2 Lines 6-14 techniques for identifying or recommending literary works (e.g., books) that correspond to user request. The user request may include search criteria (e.g., terms and phrases) entered by the user and that define characteristics of a literary work that the user desires. In some instances, the search criteria may include descriptors of a plot (e.g., suspense), a setting (e.g., Hawaii), an author (e.g., Steven King), a story arc, and/or other defining keywords (e.g., cliffhanger, action-packed, drama, etc.); Col. 15 Lines 22-32 The recommendation service 108 may operate in parallel and for multiple users at the same time. For instance, recommendations for literary works received from multiple (and possibly unique) user devices 104 may be requested and the components of the recommendation service 108 may generate the recommendations simultaneously or nearly simultaneously in real time for the multiple user devices 104. As such, the recommendation service 108 may be configured to simultaneously process a plurality of user requests and generate literary work recommendations for a plurality of users);
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 (Col. 2 Lines 14-19 This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”); 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, and storing the topic to be replied and the topic reply information in association in a database of the memory (Col. 2 Lines 14-19 This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”);
wherein the automatically generating the book recommendation information of the target recommended book comprises… 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, and generating the book recommendation information based on the target topic content; or obtaining target delivery information of the target recommended book on a corresponding target delivery platform (Col. 8 Lines 46-49 Individual literary works may be stored in the literary works database 122. That is, the literary works database 122 may be a database of literary works that stores any number of literary works; Col. 8 Lines 54-59 the recommendation service 108 may receive the literary work 200 as from a publisher, author, or other source, and may process the literary work 200 to make the literary work 200 compatible with various display formats, device platforms, and so forth to be stored in the literary works database 122; Col. 14 Lines 1-4 After searching the literary works database 122 and determining literary works that satisfy the user request, the recommendation component 118 may provide recommendations to the user 102 as recommended literary work(s); Col. 14 Lines 13-21 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106. In other instances, the recommendation service 108 may cause for delivery of a hard copy of the recommended literary work(s) to the user 102), 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 (Col. 8 Lines 54-59 the recommendation service 108 may receive the literary work 200 as from a publisher, author, or other source, and may process the literary work 200 to make the literary work 200 compatible with various display formats, device platforms, and so forth to be stored in the literary works database 122; Col. 14 Lines 1-4 After searching the literary works database 122 and determining literary works that satisfy the user request, the recommendation component 118 may provide recommendations to the user 102 as recommended literary work(s); Col. 14 Lines 13-21 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106. In other instances, the recommendation service 108 may cause for delivery of a hard copy of the recommended literary work(s) to the user 102; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”).
However, Yu does not explicitly teach the following limitations:
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, and generating the book recommendation information based on the target topic content; 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.
Lorch, in the same field of endeavor, teaches the following limitations:
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, and generating the book recommendation information based on the target topic content ([0127] At block 605, a user visits a personal download center, using the client application, or via the web. At block 640, the personal download center queries the host server for recommendations. In one implementation, the personal download center may provide information such as user ID, browsing activity, and the like, to the host server along with the request for recommendation. The host server, at block 645 generates recommendations using, for example, the recommendation engine 320. The host server provides the recommendations to the content server and/or the personal download center at block 650. The personal download center obtains information on the recommendations (e.g., e-book names, thumb nail images, blurbs, reviews, etc.) from the content server at block 655. Alternately, the content server may send additional information on the recommendations to the personal download center. At block 660, the personal download center displays the recommendations and the associated details to the user); 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.
This known technique is applicable to the system of Yu as they both share characteristics and capabilities, namely, they are directed to platforms for recommending and providing books. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Lorch would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Lorch to the teachings of Yu would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing book recommendation information for a recommended book based on content of posted book recommendation topics, such as user reviews) into similar systems.
Claim 2 (and Similarly Claim 13)
Yu further teaches the following limitations:
wherein the determining the target recommended book matched with the topic to be replied comprises: determining a plurality of book screening features based on topic content of the topic to be replied (Col. 2 Line 52-Col. 3 Line 3 A user may begin by requesting a literary recommendation and entering search criteria corresponding to a literary work he or she desires to read. The user may input a wide variety of search terms or search criteria into a request, such as freely typing a string of text describing the literary work. For instance, the request may include “I'm looking for an unresolved true-crime book that involves white-collar crime” or “Please find me an enemies to lovers novel set in the nineteen-hundreds.” Within this request, words or phrases may be identified as keyword(s) or important characteristics that describe or relate to a type of literary work the user desires to read. For instance, the techniques described herein may parse the request to identify keyword(s) using natural language processing (NLP), machine-learning algorithms, and natural language understanding (NLU) techniques. Here, terms such as “unresolved true-crime” and “white-collar crime” may be identified as keywords that describe important characteristics of a desired literary work the user would like to read; Col. 3 Lines 4-14 the identified keyword(s) may be mapped or associated with a genre, a plot, or a story arc of literary work or other keywords. For instance, the keywords “unresolved true-crime” may be associated with keywords such as “mystery” while the keywords “white-collar crime” may be associated with keywords such as “finance,” “nonviolent,” “business,” “high stakes,” and so forth. Instead of utilizing the literal search criteria (i.e., “unresolved true-crime”), or in addition to, this phrase may be associated with other commonly utilized keyword(s) to generalize or categorize the search criteria);
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 (Col. 3 Lines 15-25 Using the identified keyword(s) or other assimilated and/or closely matched keywords, the literary works database may be searched to locate recommended literary work(s). The literary works database may include a digital library storing literary works that are accessible by computing devices. The database of literary works may represent a searchable index that stores metadata in association with each of the literary works. The metadata may represent data generated from understanding characteristics, traits, or other defining features of the individual literary works and may be generated through analyzing content of the literary work; Col. 3 Lines 39-45 the metadata may indicate a plot, a genre, a story arc, and/or keyword(s) describing topics, themes, or subjects of the literary work. Discussed in detail herein, the metadata stored in association with the literary works may be used to locate literary work(s) within the literary works database that correspond to the keyword(s) or other search criteria within the request; Col. 4 Lines 32-40 using the search criteria and the keyword(s) contained in the request (or like keywords determined by computing systems), literary works that closely match the request may be flagged as possible recommended literary works. In some instances, determining recommended literary works may involve a comparison between keyword(s) of the request and keywords (or other identifiers) represented by the metadata stored in association with the individual literary works); and
determining a book satisfying a book recommendation requirement among the plurality of book recommendation collections as the target recommended book (Col. 4 Lines 40-52 the closest match may be flagged as a recommended literary work. Additionally, or alternatively, several literary works that closely match the search criteria of the request may be provided to the user as recommendations in a ranked or unranked order. The recommendation(s) may also employ the use of scores or similarity values (e.g., numbers, integers, characters, symbols, etc.) between the keyword(s) and the metadata when determining recommendations. The scores and/or similarity values may be utilized to filter literary works that fall below a threshold value. The literary works may be further parsed and filtered before being provided to the user as recommended literary works).
Claim 3 (and Similarly Claim 14)
Yu further teaches the following limitations:
wherein the book screening features comprise at least one of the following: gender information of a posting user of the topic to be replied, a book recommendation label of the topic to be replied, or operation information of a related book on which a target operation is performed by the posting user, wherein the book recommendation label is configured to indicate classification information of a book associated with the topic to be replied, and the target operation comprises at least one of the following: a reading operation or a commenting operation (Col. 3 Lines 4-14 the identified keyword(s) may be mapped or associated with a genre, a plot, or a story arc of literary work or other keywords. For instance, the keywords “unresolved true-crime” may be associated with keywords such as “mystery” while the keywords “white-collar crime” may be associated with keywords such as “finance,” “nonviolent,” “business,” “high stakes,” and so forth. Instead of utilizing the literal search criteria (i.e., “unresolved true-crime”), or in addition to, this phrase may be associated with other commonly utilized keyword(s) to generalize or categorize the search criteria; Col. 3 Lines 39-45 the metadata may indicate a plot, a genre, a story arc, and/or keyword(s) describing topics, themes, or subjects of the literary work. Discussed in detail herein, the metadata stored in association with the literary works may be used to locate literary work(s) within the literary works database that correspond to the keyword(s) or other search criteria within the request).
Claim 4 (and Similarly Claim 15)
Yu further teaches the following limitations:
the generating the book recommendation information… comprises extracting a recommendation keyword associated with the book recommendation features of the topic to be replied… and generating the book recommendation information based on the recommendation keyword (Col. 12 Lines 32-35 The recommendation component 118, or the analytics component 120, may analyze the user request and extract keyword(s) or identifiers corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”).
Lorch further teaches the following limitations:
wherein the target topic content comprises at least one of the following: topic reply content or topic recommendation content ([0127] At block 605, a user visits a personal download center, using the client application, or via the web. At block 640, the personal download center queries the host server for recommendations. In one implementation, the personal download center may provide information such as user ID, browsing activity, and the like, to the host server along with the request for recommendation. The host server, at block 645 generates recommendations using, for example, the recommendation engine 320. The host server provides the recommendations to the content server and/or the personal download center at block 650. The personal download center obtains information on the recommendations (e.g., e-book names, thumb nail images, blurbs, reviews, etc.) from the content server at block 655. Alternately, the content server may send additional information on the recommendations to the personal download center. At block 660, the personal download center displays the recommendations and the associated details to the user); and
the generating the book recommendation information based on the target topic content comprises extracting a recommendation… from the target topic content, and generating the book recommendation information based on the recommendation ([0127] The host server provides the recommendations to the content server and/or the personal download center at block 650. The personal download center obtains information on the recommendations (e.g., e-book names, thumb nail images, blurbs, reviews, etc.) from the content server at block 655. Alternately, the content server may send additional information on the recommendations to the personal download center. At block 660, the personal download center displays the recommendations and the associated details to the user).
This known technique is applicable to the system of Yu as they both share characteristics and capabilities, namely, they are directed to platforms for recommending and providing books. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Lorch would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Lorch to the teachings of Yu would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing book recommendation information for a recommended book based on content of posted book recommendation topics, such as user reviews) into similar systems.
Claim 5 (and Similarly Claim 16)
Yu further teaches the following limitations:
wherein the determining the target recommended book matched with the topic to be replied comprises: extracting book delivery information from topic content of the topic to be replied; wherein the book delivery information is configured to indicate a target delivery platform of multimedia information of a book associated with the topic to be replied (Col. 8 Lines 46-49 Individual literary works may be stored in the literary works database 122. That is, the literary works database 122 may be a database of literary works that stores any number of literary works; Col. 8 Lines 54-59 the recommendation service 108 may receive the literary work 200 as from a publisher, author, or other source, and may process the literary work 200 to make the literary work 200 compatible with various display formats, device platforms, and so forth to be stored in the literary works database 122; Col. 14 Lines 1-4 After searching the literary works database 122 and determining literary works that satisfy the user request, the recommendation component 118 may provide recommendations to the user 102 as recommended literary work(s); Col. 14 Lines 13-21 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106. In other instances, the recommendation service 108 may cause for delivery of a hard copy of the recommended literary work(s) to the user 102); and
determining the target recommended book among books delivered by the target delivery platform based on the book delivery information (Col. 8 Lines 46-49 Individual literary works may be stored in the literary works database 122. That is, the literary works database 122 may be a database of literary works that stores any number of literary works; Col. 8 Lines 54-59 the recommendation service 108 may receive the literary work 200 as from a publisher, author, or other source, and may process the literary work 200 to make the literary work 200 compatible with various display formats, device platforms, and so forth to be stored in the literary works database 122; Col. 14 Lines 1-4 After searching the literary works database 122 and determining literary works that satisfy the user request, the recommendation component 118 may provide recommendations to the user 102 as recommended literary work(s); Col. 14 Lines 13-21 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106. In other instances, the recommendation service 108 may cause for delivery of a hard copy of the recommended literary work(s) to the user 102).
Claim 6 (and Similarly Claim 17)
Yu further teaches the following limitations:
wherein the target delivery information comprises multimedia delivery information of the target recommended book and/or comment information of the multimedia delivery information (Col. 14 Lines 13-21 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106).
Claim 9 (and Similarly Claims 19 and 20)
Yu teaches the following limitations:
A reply method applied to a client, comprising: detecting a topic browsing request and determining a target recommendation topic corresponding to the topic browsing request (Col. 2 Lines 6-14 techniques for identifying or recommending literary works (e.g., books) that correspond to user request. The user request may include search criteria (e.g., terms and phrases) entered by the user and that define characteristics of a literary work that the user desires. In some instances, the search criteria may include descriptors of a plot (e.g., suspense), a setting (e.g., Hawaii), an author (e.g., Steven King), a story arc, and/or other defining keywords (e.g., cliffhanger, action-packed, drama, etc.));
obtaining topic content of the target recommendation topic (Col. 2 Lines 7-19 The user request may include search criteria (e.g., terms and phrases) entered by the user and that define characteristics of a literary work that the user desires. In some instances, the search criteria may include descriptors of a plot (e.g., suspense), a setting (e.g., Hawaii), an author (e.g., Steven King), a story arc, and/or other defining keywords (e.g., cliffhanger, action-packed, drama, etc.). This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user);
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 (Col. 2 Lines 7-19 The user request may include search criteria (e.g., terms and phrases) entered by the user and that define characteristics of a literary work that the user desires. In some instances, the search criteria may include descriptors of a plot (e.g., suspense), a setting (e.g., Hawaii), an author (e.g., Steven King), a story arc, and/or other defining keywords (e.g., cliffhanger, action-packed, drama, etc.). This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user); and
displaying the topic reply content in a topic reply area of a topic display page (Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-6 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended); and
Claim 10
Yu further teaches the following limitations:
wherein the displaying the topic reply content in the topic display page comprises: determining a target recommended book in the topic reply content, and determining a book display identifier of the target recommended book (Col. 14 Lines 1-4 After searching the literary works database 122 and determining literary works that satisfy the user request, the recommendation component 118 may provide recommendations to the user 102 as recommended literary work(s); Col. 14 Lines 9-13 when executed by a browser application running on the user device 104, data transmitted from the recommendation service 108 to the user device 104 may cause the user device 104 to display an identity of the literary works in a user interface; Col. 16 Line 62-Col. 17 Line 2 The user interface 400A may display results within a results area 404 that correspond to the user request entered into the input field 402. For instance, the results area 404 illustrates a first book 406(A), a second book 406(B), and a third book 406(c) being displayed (collectively, “the books 406”). In some instances, each of the books 406 may be displayed along with a picture of the book, a title of the book, an author of the book, or other indicator(s));
determining text content in the topic reply content, and extracting critical text information of the text content (Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 17 Lines 3-9 Additionally, the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”); and
displaying the book display identifier in a multimedia display area of the topic reply area, and displaying the critical text information in a text display area of the topic reply area (Col. 16 Line 62-Col. 17 Line 9 The user interface 400A may display results within a results area 404 that correspond to the user request entered into the input field 402. For instance, the results area 404 illustrates a first book 406(A), a second book 406(B), and a third book 406(c) being displayed (collectively, “the books 406”). In some instances, each of the books 406 may be displayed along with a picture of the book, a title of the book, an author of the book, or other indicator(s), as well as a rating of the books 406. Additionally, the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”).
Claim 11
Yu further teaches the following limitations:
wherein the method further comprises: switching to a recommendation details page displaying the target recommended book in response to a triggering operation on the book display identifier; wherein the recommendation details page comprises: a book reading page of the target recommended book and/or, a delivery page of multimedia delivery information of the target recommended book on a target delivery platform (Col. 14 Lines 14-22 the recommended literary work(s) include a link or option to review, purchase, or otherwise learn more information about the recommended literary work(s). The recommendation service 108 may further facilitate a download of the literary work in digital form to the user device 104 over the network 106. In other instances, the recommendation service 108 may cause for delivery of a hard copy of the recommended literary work(s) to the user 102; Col. 17 Lines 48-55 The user may select one of the books 406, for instance, via touching an area corresponding to one of the first book 406(A), the second book 406(B), or the third book 406(C) respectively. In response, the user interface 400A may cause the contents of the book (e.g., the book 406(A)) to be displayed. Additionally, or alternatively, the contents of the book may be downloaded to a user device (e.g., the user device 104)).
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US-10922340) in view of Lorch (US-20130185198), and further in view of Zagorie et al. (US-8423889).
Claim 7
Yu further teaches the following limitations:
the generating the topic reply information of the topic to be replied based on the target recommended book and the book recommendation information comprises: generating the topic reply information of the topic to be replied based on… the target recommended book and the book recommendation information (Col. 2 Lines 14-19 This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”).
However, Yu, in combination with Lorch, does not explicitly teach the following limitations:
wherein the method further comprises: obtaining at least one preset reply template, and determining a target reply template matched with the topic to be replied in the at least one preset reply template; and
generating the topic reply information of the topic to be replied based on the target reply template
Zagorie, in the same field of endeavor, teaches the following limitations:
wherein the method further comprises: obtaining at least one preset reply template, and determining a target reply template matched with the topic to be replied in the at least one preset reply template (Col. 4 Lines 5-9 the content store 114 maintains a template store 122 to hold collections of pre-configured templates 124(1), 124(2), . . . , and 124(N). Each template 124 is designed to layout content elements on a particular screen configuration of an associated eBook reader device 102-106; Col. 7 Lines 4-9 the templates 124 are used to dynamically create pages on demand. The templates are configured to place the content at precise locations for various screen configurations. In response to a request, a suitable template is selected and populated with content to form a page that may be served to the requesting device; Col. 7 Lines 25-28 a template may be populated with a recommendation for a particular book based on a user's previous purchase of a book by the same author, based on a user's preference for a certain genre of book, or the like); and
generating the topic reply information of the topic to be replied based on the target reply template (Col. 7 Lines 4-9 the templates 124 are used to dynamically create pages on demand. The templates are configured to place the content at precise locations for various screen configurations. In response to a request, a suitable template is selected and populated with content to form a page that may be served to the requesting device)
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the personalized book recommendation platform of Yu, in combination with Lorch, with the limitations taught by Zagorie. One of ordinary skill in the art would have been motivated to make this modification for the benefit of selecting an appropriate template to format the content according to the device capabilities, and thus allowing the user to interact with the content (Zagorie – Col. 4 Line 58-Col. 5 Line 4), and further, for presenting content based on a user’s content presentation preferences (Zagorie – Col. 7 Lines 21-24).
Claim 8
Yu further teaches the following limitations:
the generating the topic reply information of the topic to be replied based on… the target recommended book and the book recommendation information (Col. 2 Lines 14-19 This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”)
generating a second reply information based on the target recommended book and the book recommendation information (Col. 2 Lines 14-19 This search criteria entered by the user may then be used to search a database of literary works to recommend one or more literary works(s). For instance, in searching the database of literary works, literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 16 Lines 49-54 a user may insert (e.g., type) characteristics of a literary work the user would like to read. For instance, shown in FIG. 4A, the user has typed “romance enemies to lovers,” indicating that the user would like to read a romance literary work where the characters in the book start and enemies and grow to be lovers; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended. As an example, such explanation may include “the first book is recommended because this book is a romance where the main characters are enemies at first, but as the story progresses, the characters fall in love.”); and
combining the first reply information and the second reply information to obtain the topic reply information (Col. 2 Lines 14-19 literary works corresponding to the search criteria may be identified and provided to the user; Col. 13 Lines 36-41 The recommendation service 108 may also determine reasons why a literary work is recommended and may include an explanation that indicates a recommended literary work has a similar structure or similar plot corresponding to the user request; Col. 17 Lines 3-9 the first book 406(A), the second book 406(B), and the third book 406(C) may be presented with an explanation of why the book is recommended).
However, Yu, in combination with Lorch, does not explicitly teach the following limitations:
wherein the target reply template contains a plurality of filling positions;
the generating the topic reply information of the topic to be replied based on the target reply template… comprises: determining filling content of each of the filling positions based on the topic to be replied, and generating a first reply information based on the filling content;
Zagorie, in the same field of endeavor, teaches the following limitations:
wherein the target reply template contains a plurality of filling positions (Col. 4 Lines 18-19 The templates 124 define how content is to be arranged on the various displays; Col. 4 Lines 22-23 Through use of different templates, essentially the same content may be arranged differently depending on the display; Col. 7 Lines 5-9 The templates are configured to place the content at precise locations for various screen configurations. In response to a request, a suitable template is selected and populated with content to form a page that may be served to the requesting device);
the generating the topic reply information of the topic to be replied based on the target reply template… comprises: determining filling content of each of the filling positions based on the topic to be replied, and generating a first reply information based on the filling content (Col. 4 Lines 53-54 the user's device (e.g., device 102) submits a request for content from the content store 114; Col. 4 Line 62-Col. 5 Line 2 The servers 112 then process the request according to the customer services to create the content to be returned to the device. The servers 112 further select an appropriate template 124 from the template store 122 to format the content according to the device capabilities learned from the credentials in the client request. Once formatted, the servers 112 serve the pre-formatted content to the requesting device 102; Col. 7 Lines 5-9 The templates are configured to place the content at precise locations for various screen configurations. In response to a request, a suitable template is selected and populated with content to form a page that may be served to the requesting device);
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the personalized book recommendation platform of Yu, in combination with Lorch, with the limitations taught by Zagorie. One of ordinary skill in the art would have been motivated to make this modification for the benefit of selecting an appropriate template to format the content according to the device capabilities, and thus allowing the user to interact with the content (Zagorie – Col. 4 Line 58-Col. 5 Line 4), and further, for presenting content based on a user’s content presentation preferences (Zagorie – Col. 7 Lines 21-24).
Response to Arguments
Applicant’s Argument Regarding 35 USC 112(b) Rejections of Claims 9-11 and 19-20: Claim 9 has 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:
Claim 1 defines a method for automatically generating replies to topics in reading applications. This is a specific implementation of reply automatic generation technology and has a clear and specific technical scenario.
The implementation of this method relies on the processor, memory, and their interaction in the server, and includes a series of steps that need to be completed through technical means: the processor determines a target recommended book matched with the topic to be replied, and automatically generating book recommendation information of the target recommended book; the processor automatically generates topic reply information of the topic to be replied based on the target recommended book and the book recommendation information, and stores the topic to be replied and the topic reply information in association in a database of the memory. These steps, such as automatic information generation and database storage, cannot be practically performed in the human mind. Taken together, the claimed method effectively realizes the automatic reply function for topics to be replied to in reading applications.
By incorporating the above features, the claimed method for automatically generating reply to a topic in a reading application addresses the problem in the prior art - the topic of recommending books in reading applications cannot be replied to in a timely manner, resulting in users who post topics having difficulty obtaining relevant information about the books they need, thereby affecting the user experience.
Thus, Applicant submits that claim 1, as a whole, integrates the alleged abstract idea into a practical application and should not be considered as a judicial exception. Moreover, based on the above analysis, claim 1, as a whole, amounts to significantly than the alleged abstract idea in the field of target application content recommendation.
Examiner’s Response: Applicant’s arguments have been fully considered but they are not persuasive.
The steps of determining a target recommended book matched with a topic to be replied, generating book recommendation information of the target recommended book, generating topic reply information of the topic to be replied based on the target recommended book and the book recommendation information, and storing the topic to be replied and the topic reply information in association, are all part of the abstract idea, and they fall under the Certain Methods of Organizing Human Activity grouping of abstract ideas. The processor, memory, and server are generic computers, and the database is recited in a generic manner, all used as mere tools to implement the abstract idea. The “automatic” generation of information is mere automation of a manual process, and the computer is being used in its ordinary capacity to generate information. Regarding the argument that the steps cannot be practically performed in the human mind, the claims were not rejected under the Mental Processes grouping of abstract ideas. However, this grouping would also be applicable, as the steps can actually practically be performed in the human mind and with pen and paper, as a human can practically determine a target recommended book matched with a topic to be replied, and generate book recommendation information of the target recommended book, and store information such as on a piece of paper.
Regarding the argument of addressing the problem in the prior art of “the topic of recommending books in reading applications cannot be replied to in a timely manner, resulting in users who post topics having difficulty obtaining relevant information about the books they need, thereby affecting the user experience,” the automation of book recommendations is a recitation of an improvement to the abstract idea itself, and not an improvement to the functioning of the computer itself or any other technology. Further, the specification does not provide any details of how the claimed invention provides any improvement to the functioning of computer (or any other) technology. As such, the claims do not recite additional elements that integrate the abstract idea into a practical application, or that amount to significantly more than the abstract idea.
Applicant’s Argument Regarding 35 USC 102 and 103 Rejections of Claims 1-20:
The applied references do not disclose or render obvious the combination recited in amended claim 1.
Examiner’s Response: Applicant’s arguments have been considered but are moot in light of the new ground of rejection above.
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.
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/KARMA A EL-CHANTI/Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629