DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to Application No. 18/931682, filed on 10/30/2024. Claims 1-20 are currently pending and have been examined. Claims 1-20 have been rejected as follows.
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.
The 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: The claims 1-14 are a method, claims 15-17 are system, and claims 18-20 are a computer readable medium. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101.
Step 2A Prong 1: The independent claims (1, 15 and 18, taking claim 1 as a representative claim) recite:
A multimedia content recommendation method, comprising:
determining, for any book, first reading data of the book in a plurality of reading sources, the reading sources comprising at least a book recommendation special topic;
determining recommendation contribution information of the book recommendation special topic for the book based on the first reading data; and
determining a recommendation form of the book based on the recommendation contribution information.
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The claimed invention recites steps for determining a recommendation based on book related and reader related data. The steps under its broadest reasonable interpretation specifically fall under sales activities. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
Claim 1 recites no additional elements
Claim 15 recites an electronic device, comprising: a processor; and a memory, configured to store executable instructions of the processor, wherein the processor is configured to perform a multimedia content recommendation method by executing the executable instructions, comprising:
Claim 18 recites a non-transitory computer-readable storage medium having stored thereon a computer program that, when executed by a processor, causes the processor to perform a multimedia content recommendation method, comprising:
The additional elements of listed above are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application – MPEP 2106.05(f).
Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong two, the additional elements in the claims amount to no more than mere instructions to apply the judicial exception using a generic computer component.
Even when considered as an ordered combination, the additional elements of claim 1, 15, and 18 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1, 15, and 18 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1, 15, and 18 are ineligible.
Dependent claims 2-14, 16-17, and 19-20 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. §101 because the additional recited limitations fail to establish that the claims are not directed to the same abstract idea of Independent Claims 1, 15 and 18 without significantly more.
Claim 2 recites wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 3 recites wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. he limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 4 recites wherein the determining recommendation contribution information of the book recommendation special topic for the book based on the first reading data comprises: determining a reading contribution proportion of the book recommendation special topic for the book based on the total quantity of first-type readers and the total quantity of second-type readers; and if the reading contribution proportion is greater than or equal to a preset reading contribution proportion, and the total quantity of first-type readers is greater than or equal to a preset quantity of readers, determining the recommendation contribution information of the book recommendation special topic for the book at least based on the first reading conversion quantity and the first-type reader retention quantity; otherwise, determining the recommendation contribution information of the book recommendation special topic for the book at least based on the first reading conversion quantity, the second reading conversion quantity, the first-type reader retention quantity, and the second-type reader retention quantity. he limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 5 recites wherein the determining recommendation contribution information of the book recommendation special topic for the book at least based on the first reading conversion quantity and the first-type reader retention quantity comprises: determining a first reading conversion rate of the book in the book recommendation special topic based on the first reading conversion quantity and a first exposure time of target special topic content in the book recommendation special topic, the target special topic content being for recommending the book; determining a minimum reading duration between a reading duration of readers who read the book through the book recommendation special topic and a preset reading duration, and a first correction coefficient corresponding to a first exposure time; and determining the recommendation contribution information of the book recommendation special topic for the book based on the first reading conversion rate, the first-type reader retention quantity, the minimum reading duration, and the first correction coefficient. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 6 recites wherein the determining recommendation contribution information of the book recommendation special topic for the book at least based on the first reading conversion quantity, the second reading conversion quantity, the first-type reader retention quantity, and the second-type reader retention quantity comprises: determining a first reading conversion rate of the book in the book recommendation special topic and a second reading conversion rate of the book in the other reading sources based on the first reading conversion quantity, the second reading conversion quantity, a first exposure time of target special topic content in the book recommendation special topic, and a second exposure time of the book in the other reading sources, the target special topic content being for recommending the book; determining a minimum reading duration between a reading duration of readers who read the book through the book recommendation special topic and a preset reading duration, and a second correction coefficient corresponding to a second exposure time; and determining the recommendation contribution information of the book recommendation special topic for the book based on the first reading conversion rate, the second reading conversion rate, the first-type reader retention quantity, the second-type reader retention quantity, the minimum reading duration, and the second correction coefficient. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 7 recites further comprising: determining second reading data of the book after target special topic content in the book recommendation special topic is searched, the target special topic content being for recommending the book; and determining search contribution information of the book recommendation special topic for the book based on the second reading data; the determining a recommendation form of the book based on the recommendation contribution information comprises: determining the recommendation form of the book based on the recommendation contribution information and the search contribution information. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 8 recites wherein the determining second reading data of the book after target special topic content in the book recommendation special topic is searched comprises: determining an associated search term for the target special topic content in the book recommendation special topic within a second preset historical period; and determining, for each associated search term, a search time of the associated search term within the second preset historical period, and a total reading conversion quantity for the search by using the associated search term and a third reading conversion quantity of the target special topic content. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 9 recites wherein the determining search contribution information of the book recommendation special topic for the book based on the second reading data comprises: determining, for each associated search term, a search contribution proportion of the book recommendation special topic for the book under the associated search term based on the total reading conversion quantity for the search by using the associated search term and the third reading conversion quantity; and if a search time of the associated search term is greater than or equal to a preset search time, and the search contribution proportion is greater than or equal to a preset search contribution proportion, determining the search contribution information of the book recommendation special topic for the book based on the search contribution proportion, a minimum reading duration between a reading duration of readers who read the book through the target special topic content searched based on the associated search term and a preset reading duration, and a third correction coefficient corresponding to the search contribution proportion; otherwise, determining that the search contribution information of the book recommendation special topic for the book is 0.
Claim 10 recites wherein if there are a plurality of associated search terms for the target special topic content in the book recommendation special topic, the determining search contribution information of the book recommendation special topic for the book based on the second reading data further comprises: using a maximum value of search contribution information of the target special topic content under each of the associated search terms as the search contribution information of the book recommendation special topic for the book. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 11 recites wherein the book recommendation special topic comprises topic content, book list content, and multimedia content for recommending the book, and the recommendation contribution information of the book recommendation special topic for the book comprises first recommendation contribution information of the topic content for the book, second recommendation contribution information of the book list content for the book, and third recommendation contribution information of the multimedia content for the book; and the determining a recommendation form of the book based on the recommendation contribution information comprises: determining, based on the first recommendation contribution information, the second recommendation contribution information, and the third recommendation contribution information, the recommendation form of the book as at least one of the topic content, the book list content, and the multimedia content. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 12 recites wherein the book recommendation special topic comprises topic content, book list content, and multimedia content for recommending the book; the recommendation contribution information of the book recommendation special topic for the book comprises first recommendation contribution information of the topic content for the book, second recommendation contribution information of the book list content for the book, and third recommendation contribution information of the multimedia content for the book; the search contribution information of the book recommendation special topic for the book comprises first search contribution information of the topic content for the book, second search contribution information of the book list content for the book, and third search contribution information of the multimedia content for the book; and the determining a recommendation form of the book based on the recommendation contribution information and the search contribution information comprises: determining, based on the first recommendation contribution information, the second recommendation contribution information, and the third recommendation contribution information, and the first search contribution information, the second search contribution information, and the third search contribution information, the recommendation form of the book as at least one of the topic content, the book list content, and the multimedia content.
Claim 13 recites wherein if a recommendation form of the book is to recommend the book through target special topic content in the book recommendation special topic, the target special topic content comprises at least a cover, a name, and a recommendation text of the book. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 14 recites further comprising: determining, based on attributes and recommendation forms of historical books, attributes of to-be-recommended books suitable for topic content, book list content, and multimedia content in the book recommendation special topic. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 16 recites wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 17 recites wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 19 recites wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 20 recites wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 7, 11, 13-16, 18-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lorch (US20130185198).
Regarding claim 1, Lorch discloses:
A multimedia content recommendation method, comprising: determining, for any book, first reading data of the book in a plurality of reading sources, the reading sources comprising at least a book recommendation special topic; [0150] The process starts at block 1105. At block 1110, a list of e-books consumed by a user may be selected. For example, a query may be created and executed on the analytics database 370 to select the list of e-books consumed by a user during the last three months. At block 1120, one or more criteria for ranking the identified e-books may be selected. Example criteria can include: percent completion, reading location, e-books shared, e-books gifted, time of e-book consumption, rate of e-book consumption, bookmarks, highlights, and the like. At block 1125, the weights for each of the selected criteria may be obtained. For example, percentage completion criteria may be assigned a higher weight of 40%, reading location may be assigned 5%, e-books shared may be assigned 10%, e-books gifted 10%, time of e-book consumption 5% and rate of e-book consumption 30%. The examiner interprets the selected list of ebooks consumer by a user in the last 3 months as the special topic.
determining recommendation contribution information of the book recommendation special topic for the book based on the first reading data; and [0159] At block 1135, the e-books in the list are ranked based on the e-book score. At block 1140, the top x number of e-books in the list are selected, and other e-books similar to the selected x number of e-books are identified. The similar e-books may be identified based on matching of metadata and/or other attributes.
determining a recommendation form of the book based on the recommendation contribution information. [0159] At block 1145, the identified e-books are provided as recommendations to the user. Periodically, an update trigger may be generated to update the recommendation. The update trigger may be an activity relating to the e-book, such as an e-book download, sharing, gifting, adding to shelf, and the like. At decision block 1150, if such a trigger is received, the process moves back to block 1110. If no trigger is received, the process ends at block 1155.
Regarding claim 2, Lorch discloses the limitations set forth above and further discloses:
wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; [0054] The sharing module 225 may include the necessary tools, plug-ins or interfaces to allow sharing of e-books, comments, messages, posts, and/or the like with other users of the ICPM system and/or external sites. Various application programming interfaces (APIs) may be implemented to facilitate the interaction between the ICPM client application and peers, and external sites. In one implementation, the sharing module 225 may also report each sharing activity to the analytics module such that data relating to the sharing activities can be collected and analyzed.
determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. [0084] In another implementation, the content consumption pattern detector module 328 can keep track of the bread crumb trail of readers as they engage in reading activities on the ICPM system. The bread crumb trail can show the reading history of a reader and identify a book or events that led to another book or event, and so on. The pattern detector module 328 can identify and define various communities of readers, how the communities relate to each other, and how the communities change over time. Such patterns and insights may be valuable for promoting books and reading in general. [0085] By way of another example, the content consumption pattern detector module 328, may analyze consumption data to determine the average amount of time a user takes to read an electronic page, average number of electronic pages the user reads in a single session, time lapse between reading sessions on weekdays, weekends, day, night, and/or the like. In one implementation, the pattern detected may then be used to adjust parameters such as the qualify-as-read parameter, the triggering of charge events, and/or the like. and see [0086-87]
Regarding claim 7, Lorch discloses the limitations set forth above and Lorch further discloses:
further comprising: determining second reading data of the book after target special topic content in the book recommendation special topic is searched, the target special topic content being for recommending the book; and determining search contribution information of the book recommendation special topic for the book based on the second reading data; the determining a recommendation form of the book based on the recommendation contribution information comprises: determining the recommendation form of the book based on the recommendation contribution information and the search contribution information. [0126] Once e-books are stored in the content server, the e-books are made available for download via the personal download center, and in some instances, via other online websites. In one implementation, a user can visit the personal download center to browse through the e-book catalog, search and/or select a specific e-book or e-books for download. In another implementation, the personal download center can be customized for the user such that the user can view e-books that are selected for the user based on the user's profile. FIG. 6 is a logic flow diagram illustrating an exemplary method of downloading an e-book from a personal download center in one embodiment of the ICPM system. [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. At block 665, the user requests to download one or more e-books from the recommendations, or from the catalog.
Regarding claim 11, Lorch discloses the limitations set forth above and further discloses:
wherein the book recommendation special topic comprises topic content, book list content, and multimedia content for recommending the book, and the recommendation contribution information of the book recommendation special topic for the book comprises first recommendation contribution information of the topic content for the book, second recommendation contribution information of the book list content for the book, and third recommendation contribution information of the multimedia content for the book; and [0150] The process starts at block 1105. At block 1110, a list of e-books consumed by a user may be selected. For example, a query may be created and executed on the analytics database 370 to select the list of e-books consumed by a user during the last three months. At block 1120, one or more criteria for ranking the identified e-books may be selected. Example criteria can include: percent completion, reading location, e-books shared, e-books gifted, time of e-book consumption, rate of e-book consumption, bookmarks, highlights, and the like. At block 1125, the weights for each of the selected criteria may be obtained. For example, percentage completion criteria may be assigned a higher weight of 40%, reading location may be assigned 5%, e-books shared may be assigned 10%, e-books gifted 10%, time of e-book consumption 5% and rate of e-book consumption 30%. The examiner interprets the selected list of ebooks consumer by a user in the last 3 months as the special topic.
Regarding claim 13, Lorch discloses the limitations set forth above and further discloses:
wherein if a recommendation form of the book is to recommend the book through target special topic content in the book recommendation special topic, the target special topic content comprises at least a cover, a name, and a recommendation text of the book. (shown in Figure 12B interface 1255 recommended books with covers and names and popout giving summary of the book)
Regarding claim 14, Lorch discloses the limitations set forth above and further discloses:
further comprising: determining, based on attributes and recommendation forms of historical books, attributes of to-be-recommended books suitable for topic content, book list content, and multimedia content in the book recommendation special topic. [0150] The process starts at block 1105. At block 1110, a list of e-books consumed by a user may be selected. For example, a query may be created and executed on the analytics database 370 to select the list of e-books consumed by a user during the last three months. At block 1120, one or more criteria for ranking the identified e-books may be selected. Example criteria can include: percent completion, reading location, e-books shared, e-books gifted, time of e-book consumption, rate of e-book consumption, bookmarks, highlights, and the like. At block 1125, the weights for each of the selected criteria may be obtained. For example, percentage completion criteria may be assigned a higher weight of 40%, reading location may be assigned 5%, e-books shared may be assigned 10%, e-books gifted 10%, time of e-book consumption 5% and rate of e-book consumption 30%. The examiner interprets the selected list of ebooks consumer by a user in the last 3 months as the special topic.
Regarding claim 15, Lorch discloses:
An electronic device, comprising: a processor; and a memory, configured to store executable instructions of the processor, wherein the processor is configured to perform a multimedia content recommendation method by executing the executable instructions, comprising: (shown in the system of Figure 1 and the memory storing instructions 280 in Figure 2)
determining, for any book, first reading data of the book in a plurality of reading sources, the reading sources comprising at least a book recommendation special topic; [0150] The process starts at block 1105. At block 1110, a list of e-books consumed by a user may be selected. For example, a query may be created and executed on the analytics database 370 to select the list of e-books consumed by a user during the last three months. At block 1120, one or more criteria for ranking the identified e-books may be selected. Example criteria can include: percent completion, reading location, e-books shared, e-books gifted, time of e-book consumption, rate of e-book consumption, bookmarks, highlights, and the like. At block 1125, the weights for each of the selected criteria may be obtained. For example, percentage completion criteria may be assigned a higher weight of 40%, reading location may be assigned 5%, e-books shared may be assigned 10%, e-books gifted 10%, time of e-book consumption 5% and rate of e-book consumption 30%. The examiner interprets the selected list of ebooks consumer by a user in the last 3 months as the special topic.
determining recommendation contribution information of the book recommendation special topic for the book based on the first reading data; and [0159] At block 1135, the e-books in the list are ranked based on the e-book score. At block 1140, the top x number of e-books in the list are selected, and other e-books similar to the selected x number of e-books are identified. The similar e-books may be identified based on matching of metadata and/or other attributes.
determining a recommendation form of the book based on the recommendation contribution information. [0159] At block 1145, the identified e-books are provided as recommendations to the user. Periodically, an update trigger may be generated to update the recommendation. The update trigger may be an activity relating to the e-book, such as an e-book download, sharing, gifting, adding to shelf, and the like. At decision block 1150, if such a trigger is received, the process moves back to block 1110. If no trigger is received, the process ends at block 1155.
Regarding claim 16, Lorch discloses the limitations set forth above and further discloses:
wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; [0054] The sharing module 225 may include the necessary tools, plug-ins or interfaces to allow sharing of e-books, comments, messages, posts, and/or the like with other users of the ICPM system and/or external sites. Various application programming interfaces (APIs) may be implemented to facilitate the interaction between the ICPM client application and peers, and external sites. In one implementation, the sharing module 225 may also report each sharing activity to the analytics module such that data relating to the sharing activities can be collected and analyzed.
determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. [0084] In another implementation, the content consumption pattern detector module 328 can keep track of the bread crumb trail of readers as they engage in reading activities on the ICPM system. The bread crumb trail can show the reading history of a reader and identify a book or events that led to another book or event, and so on. The pattern detector module 328 can identify and define various communities of readers, how the communities relate to each other, and how the communities change over time. Such patterns and insights may be valuable for promoting books and reading in general. [0085] By way of another example, the content consumption pattern detector module 328, may analyze consumption data to determine the average amount of time a user takes to read an electronic page, average number of electronic pages the user reads in a single session, time lapse between reading sessions on weekdays, weekends, day, night, and/or the like. In one implementation, the pattern detected may then be used to adjust parameters such as the qualify-as-read parameter, the triggering of charge events, and/or the like. and see [0086-0087]
Regarding claim 18, Lorch discloses:
A non-transitory computer-readable storage medium ([0180] Storage devices 2132 may employ any number of tangible, non-transitory storage devices or systems such as fixed or removable magnetic disk drive, an optical drive, solid state memory devices and other processor-readable storage media.) having stored thereon a computer program that, when executed by a processor, causes the processor to perform a multimedia content recommendation method, comprising: (shown in the system of Figure 1 and the memory storing instructions 280 in Figure 2)
determining, for any book, first reading data of the book in a plurality of reading sources, the reading sources comprising at least a book recommendation special topic; [0150] The process starts at block 1105. At block 1110, a list of e-books consumed by a user may be selected. For example, a query may be created and executed on the analytics database 370 to select the list of e-books consumed by a user during the last three months. At block 1120, one or more criteria for ranking the identified e-books may be selected. Example criteria can include: percent completion, reading location, e-books shared, e-books gifted, time of e-book consumption, rate of e-book consumption, bookmarks, highlights, and the like. At block 1125, the weights for each of the selected criteria may be obtained. For example, percentage completion criteria may be assigned a higher weight of 40%, reading location may be assigned 5%, e-books shared may be assigned 10%, e-books gifted 10%, time of e-book consumption 5% and rate of e-book consumption 30%. The examiner interprets the selected list of ebooks consumer by a user in the last 3 months as the special topic.
determining recommendation contribution information of the book recommendation special topic for the book based on the first reading data; and [0159] At block 1135, the e-books in the list are ranked based on the e-book score. At block 1140, the top x number of e-books in the list are selected, and other e-books similar to the selected x number of e-books are identified. The similar e-books may be identified based on matching of metadata and/or other attributes.
determining a recommendation form of the book based on the recommendation contribution information. [0159] At block 1145, the identified e-books are provided as recommendations to the user. Periodically, an update trigger may be generated to update the recommendation. The update trigger may be an activity relating to the e-book, such as an e-book download, sharing, gifting, adding to shelf, and the like. At decision block 1150, if such a trigger is received, the process moves back to block 1110. If no trigger is received, the process ends at block 1155.
Regarding claim 19, Lorch discloses the limitations set forth above and further discloses:
wherein the determining first reading data of the book in a plurality of reading sources comprises: determining reading sources of the book in a reading application, the reading sources comprising at least the book recommendation special topic; [0054] The sharing module 225 may include the necessary tools, plug-ins or interfaces to allow sharing of e-books, comments, messages, posts, and/or the like with other users of the ICPM system and/or external sites. Various application programming interfaces (APIs) may be implemented to facilitate the interaction between the ICPM client application and peers, and external sites. In one implementation, the sharing module 225 may also report each sharing activity to the analytics module such that data relating to the sharing activities can be collected and analyzed.
determining a total quantity of first-type readers who read the book through the book recommendation special topic within a first preset historical period, and a first reading conversion quantity and a first-type reader retention quantity of the book in the book recommendation special topic; and determining a total quantity of second-type readers who read the book through other reading sources within the first preset historical period, and a second reading conversion quantity and a second-type reader retention quantity of the book in the other reading sources. [0084] In another implementation, the content consumption pattern detector module 328 can keep track of the bread crumb trail of readers as they engage in reading activities on the ICPM system. The bread crumb trail can show the reading history of a reader and identify a book or events that led to another book or event, and so on. The pattern detector module 328 can identify and define various communities of readers, how the communities relate to each other, and how the communities change over time. Such patterns and insights may be valuable for promoting books and reading in general. [0085] By way of another example, the content consumption pattern detector module 328, may analyze consumption data to determine the average amount of time a user takes to read an electronic page, average number of electronic pages the user reads in a single session, time lapse between reading sessions on weekdays, weekends, day, night, and/or the like. In one implementation, the pattern detected may then be used to adjust parameters such as the qualify-as-read parameter, the triggering of charge events, and/or the like. and see [0086-0087]
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 3, 17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lorch (US20130185198) in view of Seo (US 11615155).
Regarding claim 3, Lorch discloses the limitations set forth above. While Lorch discloses the recommendation of books based on collected data about a reader and corresponding books, the reference does not disclose:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages.
However Seo teaches:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. (Col. 13 lines 30-45) Herein, as an example of the operations for retrieving or calculating the information on the specific complete-reading probability, the server 100 performs a process of acquiring a first cardinal number of a first part of the users whose specific reference read pages are equal to or greater than a first threshold, a process of acquiring a second cardinal number of a second part of the users whose specific reference read pages are equal to or greater than a second threshold
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the recommendation in Lorch to include wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages, as taught in Seo, in order to improve the probability of the book being completed by improving the match between the reader and the book (see Col. 1 lines 37-50
Regarding claim 17, Lorch discloses the limitations set forth above. While Lorch discloses the recommendation of books based on collected data about a reader and corresponding books, the reference does not disclose:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages.
However Seo teaches:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. (Col. 13 lines 30-45) Herein, as an example of the operations for retrieving or calculating the information on the specific complete-reading probability, the server 100 performs a process of acquiring a first cardinal number of a first part of the users whose specific reference read pages are equal to or greater than a first threshold, a process of acquiring a second cardinal number of a second part of the users whose specific reference read pages are equal to or greater than a second threshold
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the recommendation in Lorch to include wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages, as taught in Seo, in order to improve the probability of the book being completed by improving the match between the reader and the book (see Col. 1 lines 37-50
Regarding claim 20, Lorch discloses the limitations set forth above. While Lorch discloses the recommendation of books based on collected data about a reader and corresponding books, the reference does not disclose:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages.
However Seo teaches:
wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages. (Col. 13 lines 30-45) Herein, as an example of the operations for retrieving or calculating the information on the specific complete-reading probability, the server 100 performs a process of acquiring a first cardinal number of a first part of the users whose specific reference read pages are equal to or greater than a first threshold, a process of acquiring a second cardinal number of a second part of the users whose specific reference read pages are equal to or greater than a second threshold
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the recommendation in Lorch to include wherein the first reading conversion quantity is a quantity of first-type readers who read the book through the book recommendation special topic and whose number of read pages is greater than a preset number of pages; and the second reading conversion quantity is a quantity of second-type readers who read the book through the other reading sources and whose number of read pages is greater than the preset number of pages, as taught in Seo, in order to improve the probability of the book being completed by improving the match between the reader and the book (see Col. 1 lines 37-50
Subject Matter Free of Prior Art
Claims 4, 5, 6, 8, 9, 10, and 12 are determined to be free of prior art. However, the claims are objected to as they depend from independent claim 1 which is rejected under 35 USC 102/103. Further, claims 4-6, 8-10, and 12 are rejected under 35 USC 101 for reciting ineligible subject matter. Therefore, the claims are not allowable as written.
In addition to the references applied above, Lorch and Seo, the closest prior art of record to the dependent claims 4-6, 8-10 and 12 is as follows:
Wang CN 106095867 discloses receiving a book search request comprising search terms and using historical action data related to the user along with the search terms to provide a book recommendation. However, the reference does not disclose a reading contribution portion, a first reading conversion rate based on duration, or search contribution information as required in the claimed invention.
XU CN 110647689 discloses a search input module, a keyword extraction module, book recommendation module, and a purchase confirmation module for recommendation book information to the end user. However, the reference does not disclose a reading contribution portion, a first reading conversion rate based on duration, or search contribution information as required in the claimed invention.
“STUDY ON BOOK RECOMMENDATION SYSTEM” (NPL) discloses the Item Based Cooperative Filtering methodology is described in [13] which is the outcome of combining Cooperative Filtering and Item Based Filtering is used by the RS in this investigation. The rating matrix is used by collaborative filtering to determine ratings, while book attributes are primarily used by item-based search to determine how similar two books are to one another. Numerous uses of the cooperative filtering technology have proved successful. By taking into account opinions in the form of preference ratings, the Collaborative Filtering methodology forecast user preferences for things in an extremely word-of-mouth manner (see page 4). However, the reference does not disclose a reading contribution portion, a first reading conversion rate based on duration, or search contribution information as required in the claimed invention.
It was found that no references alone or in combination, neither anticipates, reasonable teaches, nor renders obvious the above claims 4-6, 8-10 and 12.
Therefore, none of the cited references disclose or render obvious each and every feature of the claimed invention and the claimed invention is determined to be free of the prior art. Although individually the claimed features could be taught, any combination of references would teach the claimed limitations using a piecemeal analysis, since references would only be combined and deemed obvious based on knowledge gleaned from the applicant's disclosure. Such a reconstruction is improper (i.e., hindsight reasoning). See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). The examiner emphasizes that it is the interrelationship of the limitations that renders these claims free of the prior art/additional art.
Therefore, it is hereby asserted by the Examiner that, in light of the above, that the claims 4-6, 8-10 and 12 are free of prior art as the references do not anticipate the claims and do not render obvious any further modification of the references to a person of ordinary skill in art.
Relevant Prior Art
US 20150006258 discloses providing book recommendations based on the reader’s reading activity
Conclusion
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VICTORIA E. FRUNZI
Primary Examiner
Art Unit TC 3689
/VICTORIA E. FRUNZI/ Primary Examiner, Art Unit 3689
Prosecution Insights