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 .
DETAILED ACTION
Response to Arguments
This communication is in response to the Amendment filed on 9/3/2026.
Rejection of Claims 2, 3, 16, and 20 under 35 U.S.C. 112
Applicant’s Arguments:
Applicant argues that the amendments addressed the 112b issues.
Examiner’s Response:
The claim amendments resolve the 112b issues and the 112b rejections are withdrawn.
Rejection of Claims 1-7 and 14-20 under 35 U.S.C. 101
Applicant’s Arguments:
Per Step 2A, prong 1, Applicant argues the claimed invention does not recite an abstract idea, because the claimed coordinated, identifier-linked, two-stage client-server exchange-in which a specific message identifier serves as the linking mechanism between a pushed notification and the subsequent retrieval of paired article content and explanatory second data-constitutes a concrete technical architecture for personalized push messaging, not a mental process or a method of organizing human behavior that could be performed by a human without a computer.
Per Step 2A, prong 2, Applicant argues the recited "identifier of the first message" provides a concrete technical mechanism: it links the terminal's post-selection request specifically to the prior push message, enabling the server to retrieve both the target article and second data that is related to the first data of that particular message. This is not mere automation of a pre-existing human practice-no human can perform an identifier-based two- stage network retrieval that simultaneously delivers article content and contextually linked explanatory data in response to a specific message identifier. The claims thus impose a specific, technical constraint on how the push-notification system operates, improving the reliability and personalization of the recommendation flow in a way that is tied to the concrete operation of a distributed client-server network architecture. Applicant further argues No human actor can: transmit a structured push message comprising a machine-readable recommendation reason field and a message identifier; receive an identifier-bearing request from a terminal; perform a server-side lookup using that identifier to simultaneously retrieve full article content and related second data; and transmit both to the terminal in a coordinated network response. These steps are fundamentally tied to the operation of the disclosed communication system and cannot be practically performed outside of it.
Per step 2B, Applicant agues the identifier-linked retrieval mechanism-whereby the terminal's request carries the identifier of the first message and the server uses that identifier to jointly retrieve article content and second data related to the first data-is not a well-understood, routine, or conventional activity. The claimed combination of elements working together to achieve personalized, interpretable push messaging represents a specific technical solution to a technical problem, and thus amounts to significantly more than any alleged abstract idea.
Examiner’s Response:
Applicant's arguments have been fully considered but they are not persuasive.
Per Step 2A, Prong 1, the previous office action specifies the limitations directed to abstract ideas/judicial exceptions, specifically Certain Methods of Organizing Human Activity and Mental Processes. Applicant’s argued coordinate, identifier-link, two stage client-server exchange are a long-standing commercial practice. Retrieval of any article and related information of the article, even manually, needs an identifier to link the article and related information. For example, a marketing staff presents a client with a list/catalog of titles of advertised articles. Once the client selects the title of a particular article, the staff can use the identifier (e.g., index number) of the article/title to retrieve and present the full article and related information (e.g., estimated interests of related topics). The identifier associated with the title is necessarily needed to locate the subsequent information, the full article and the related information. In other words, without the identifier of the initial title of the article, the staff would not be able to identify the full article and related information out of many articles. In addition, initially presenting the client with the title of the article, and after selecting (analogous to a user’s click on the electronic pushed article), subsequently presenting the full article and related information is a long-standing practice. Therefore, Applicant’s argued identifier-linked, two stage process is not rooted in computer, but instead directed to Certain Methods of Organizing Human Activity, specifically commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Further, the practices of determining the target/advertised article and related information corresponding to the target/advertised article including a recommendation reason can be practically performed by a human being (observation, evaluation, judgment, and/or opinion). In fact, these practices have been commonly performed by any marketing/advertising/business personnel. Further, Applicant’s argument regarding “client-server” is directed to additional elements falling under “apply it”, which has been addressed under step 2A, prong 2. The mere nominal recitation of a generic server and a client device does not take the claim out of the abstract ideas, and in other words does not negate nature of Certain Methods of Organizing Human Activity and Mental processes.
Per Step 2A, Prong 2, Applicant continues to argue a pre-existing human practice cannot perform an identifier-based two stage network retrieval that simultaneously delivers article content and contextually linked explanatory data. As explained above, using an identifier of a title of an article to retrieve both the full article and the linked data, and presenting these post-selection contents together is a long-standing practice. The additional element of server and the user device to establish the claimed client-server mechanism is directed to “apply it,” which is simply implementing an abstract idea on a generic computer. Instead of having a marketing staff to retrieve and present the title, article, and related information, the claimed invention uses a server to perform these functions. Instead of having an in-person client, the claimed invention uses a client device to send electronic requests and receive electronic information. The focus of the claims is not on an improvement of functioning of the computer itself or any other technology, but on certain abstract ideas that use computers as tools. Regarding Applicant’s argument that a human cannot transmit a structured push message comprising a machine-readable recommendation reason field and cannot receive an identifier-bearing request from a terminal, fields of a messages, and other typical components of electronic messages are still directed to “apply it,” because these components are nominal recitations when implementing the abstract ideas in a computer and network environment. For example, instead of presenting a title of an article and a recommendation reason at an in-person setting to a client, the title and the recommendation are encapsulated in a message and a network message is necessarily encoded into fields according to a transmission protocol and readably by a computer. The steps are not rooted in computer technology, but instead the computer/network-related components in the claims are recited at a high level of generality and are merely invoked as tools to perform existing commercial/mental practices. Simply implementing the abstract ideas on a generic computer and network is not a practical application of the abstract ideas (see a similar example for Certain Methods of Organizing Human Activity, USPTO 35 U.S.C. 101 official Example 42 regarding managing medical records using a server and network-based devices).
Per Step 2B, Applicant argues that the identifier-linked retrieval mechanism-whereby the terminal's request carries the identifier of the first message and the server uses that identifier to jointly retrieve article content and second data related to the first data-is not a well-understood, routine, or conventional activity. However, the well-understand, routine and conventional (WURC) analysis is only applicable to additional elements directed to “insignificant extra-solution activity” under step 2A, Prong 2. Applicant’s argued limitations are directed to abstract ideas of Certain Methods of Organizing Human Activity and Mental Processes. These limitations are not additional elements, let alone additional elements under “insignificant extra-solution activity.” In the previous office action and this office action, the additional elements that are insignificant extra-solution activity (MPEP 2106.05(g)) in step 2A, Prong 2, are reevaluated in Step 2B using WURC. Specifically, the claim limitations, “sending, by the terminal, user behavior information of a user to the server,” are merely receiving or transmitting data over a network, which are mere judicial/court-recognized well-understood, routine, conventional activity, and remains insignificant extra-solution activity even upon reconsideration (See MPEP 2106.05(d)(II)). Applicant argues for evidence for such conclusion. Using Judicial/court-recognized WURC activities are evidence-based, and in other words a factual determination. Receiving or transmitting data over a network is judicial/court-recognized WURC (See MPEP 2106.05(d)(II): “Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014)”). Further, Applicant argues the claimed combination of elements working together to achieve personalized, interpretable push messaging represents a specific technical solution to a technical problem, and thus amounts to significantly more than any alleged abstract idea. This is mischaracterization of the claimed invention, because the claims are regarding long standing practices of abstract ideas and pre-existing human/business operations. The claimed invention just merely uses generic computers to implement these long-standing practices on an electronic network environment. The claimed components of the computers/network are necessarily involved as tools, and this is different from providing a technological solution to a technological problem. Personalized marketing and target articles are fundamental economic practice long prevalent in commerce systems as a building block of a modern economy. The Applicant’s argued improvement from a server-client network mechanism to implement these fundamental economic practices is an improvement to the abstract idea itself, rather than pertaining to an improvement to a computer functioning or any other technology or technical field.
The 101 rejections are maintained.
Rejection of Claims 1-7 and 14-20 under 35 U.S.C. 103
Applicant’s Arguments:
Applicant argues that Moon does not disclose a request that carries an identifier of a prior push message and causes the server to jointly retrieve both the target article content and second data related to the first data of that message. Applicant further cites ¶¶ [0035-0040] and argues Moon's related content section is generated based on topical similarity to the currently read article, not based on any identifier linking back to the initial push message or its first data. Applicant further argues Moon's topically related articles are not "second data related to the first data" in the sense required by the claims.
Applicant argues the provided rationale does not explain why a skilled artisan would specifically modify Bitran's push notification system to carry a first-message identifier in the post-click request such that the server uses that identifier to simultaneously retrieve both the article content and second data related to the original recommendation reason. Applicant further argues the cited motivation addresses a general desire to provide post-click recommendations, but does not address the specific identifier-based linking mechanism that is central to the claimed invention.
Examiner’s Response:
Applicant's arguments have been fully considered but they are not persuasive.
As explained in the Examiner’s response to Applicant’s argument regarding the 101 rejections, the identifier of a message for a title of an article is necessarily needed to locate the subsequent information, the full article and the related information of the article. Specifically, Moon teaches a title and synopsis of an article (Fig.2, 206) is displayed as a first message. After user selects the title/synopsis 204, the full article (Fig.3, 304 and 306) and related information (Fig.3, 302) as a second message are displayed. Without the identifier of the first message (selected title/synopsis), the second message would not be able to identify the right full article to display. The identifier, in Applicant’s argument, to link the first message and the second message is necessarily required to link the title/synopsis of the article and the full article. In other words, out of all articles, the right full article is identified via referencing/linking to the first message for the title of the selected article (Moon, Figs.1, 2, 3; ¶ [0035-0036], each news result includes, at least, a title 204 and an abstract 206. Title 204 provides a short description of the content of the news article, and the abstract 206 provides a synopsis of the content of the news article. Once the user clicks on a news article, the Internet browser accesses the referenced webpage to present the news article. In one embodiment, the textual content of the news article is referred to herein as the body of the news article. In other embodiments, the news article include one or more of a title, a body, a summary, one or more pictures, a video clip, user comments, statistical information about the page, etc. On the right side of the page, an advertising area includes a list of advertisements, which are sometimes related to the topic of the search). The reference to the first message for the title of the article is the identifier of the first message.
Moon teaches displaying related information (Fig,3, 302) in the second message. Related articles in the related information 302 are retrieved and displayed together with the full article (304 and 306). The retrieval is via referencing to the selected article title in the first message. In other words, out of all articles, the right related articles are identified via referencing/linking to the first message for the title of the selected article. The reference to the first message for the title of the article is the identifier of the first message. Therefore, Moon teaches using the identifier of the first message to retrieve the full article and the related information in the second message as claimed. Further, the related information 302 includes related articles to the title of the selected article in the first message ¶ [0038-0040], FIG. 3 shows a news article with links to related content, according to one embodiment. A typical news article includes, at least, a title 304 and a body 306. The title 304 provides a headline for the article, and the body 306 includes a textual description of the news article. In some cases, the news article may include one or more pictures, and one or more multimedia segments. Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy …). The first pushed/target/selected content/article and first data (a reason of the pushed/target/selected content/article, see the underlined bolded teachings) as claimed are taught by Bitran (Fig. 7, a push notification/article 710 and a recommendation information/reason 720 (corresponding to the claimed first data): “Here is a local event for your favorite workout activity that fits your fitness level. Your weekend is free.”; Fig. 9, a push notification/article 910 and a recommendation information/reason: “Here is some news about one of your favorite workout activities.” Fig.10, a push notification/article 1010/1020 and a recommendation information/reason: “People who suffer from similar conditions like you read these.” Fig.11, a push notification/article 1110/1120/1130/1140 and a recommendation information/reason: “Consider the following insights regarding health advisories”). The first data in the first message is the recommendation reason/topic of the pushed/target/selected content/article. Moon teaches, for post-clicking of the first message (Fig.2), the related information 302 in the second message (Fig.3), corresponding to the claimed second data, are recommended additional articles related to the topic/reason of the pushed/target/selected article in the first message. Since the additional related article(s) 302 as second data in the second message in Moon is related to the topic/reason of the pushed/target/selected article in the first message and the first data is the topic/reason of the pushed/target/selected article, the second data is related to the first data as claimed.
Regarding Applicant’s argument of lack of reasons to combine the prior art, the previous office action species both KSR(G) and KSR(A) as reasons for the combination. Specifically, Bitran teaches displaying a pushed/target article/content (first content) for a user to click and a recommendation reason/topic of the pushed/target article/content (first data) in the first message. However, Bitran does not explicitly disclose the claim limitations regarding post-click of the pushed article. Moon teaches, after clicking the pushed/target article in the first message, using the identifier/reference to the clicked article in the first message, to retrieve and display the full article and the related information related to the topic of the clicked article in the first message (second data). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine post-click operations including displaying a full article and related information via a reference/identifier to the first message as taught by Moon into clicking a pushed article displayed along with a recommendation reason/topic of the pushed article as taught by Bitran, such that a pushed article and a recommendation reason/topic for the article would be displayed and, after clicking the article, the full article and related information relevant to the topic/reason would be displayed. One of ordinary skill in the art would have been motivated to do so because Bitran recognizes that it would have been advantageous to provide post-click recommendation information along with a recommended/pushed article (¶ [0005-0006], Recommending interesting news articles to users has become extremely important for internet providers looking to maintain users' interest … methods to engage users after their initial visit is largely under explored … This process is referred to herein as post-click news recommendation, which has the goal of promoting users' navigation to other web pages … Therefore, an effective post-click news recommendation is critical to online news websites; ¶ [0049], Given a seed article s, the goal of the method to generate post-click news recommendation is to identify a set of candidate article;). (KSR(G), TSM, MPEP 2143). Additionally, one of ordinary skill in the art would have been motivated to do so because this is combining prior art elements according to known methods to yield predictable results, specifically, combining known methods of recommendation for articles to yield predictable results (KSR(A), MPEP 2143). Regarding Applicant’s arguments of identifier-based linking mechanism, the explanation regarding the teachings of the identifier has been addressed previously on pages 7-8 of this office action.
The 103 rejections are maintained.
DETAILED ACTION
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-7 and 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: Exemplary claim 15 is directed to a method/process.
Step 2A: Prong 1:
The following claim limitations are Certain Methods of Organizing Human Activity, specifically commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions):
“determining, … based on the user behavior information, target article information and first data corresponding to the target article information, wherein the first data comprises a recommendation reason field, and the first data is related to the target article information and the user behavior information;
generating … a first message based on the target article information and the first data;
receiving … the first message …, wherein the first message comprises the target article information and the first data;
displaying … a first interface, wherein the first interface comprises a first recommendation, the first recommendation comprises first content and recommendation information corresponding to the first data, and the first content is obtained based on the target article information;
receiving … a first operation on the first recommendation;
sending … a first request to the server in response to the first operation, wherein the first request comprises an identifier of the first message, the first request requests … to obtain content of a target article and second data based on the identifier of the first message, and the second data is related to the first data;
obtaining … the content of the target article and the second data based on the first request; sending … the target article and second data to the terminal;
sending … the content the target article and the second data to the terminal;
receiving … the content of the target article and the second data that are sent …; and
displaying … a second interface, wherein the content of the target article and recommendation information corresponding to the second data are displayed on the second interface.”
Moreover, the following claim limitations are Mental Processes (observation, evaluation, judgment, and/or opinion):
“determining … based on the user behavior information, target article information and first data corresponding to the target article information, wherein the first data comprises a recommendation reason field, and the first data is related to the target article information and the user behavior information.”
Therefore, the claim recites an abstract idea.
Step 2A, Prong 2: the additional elements individually or as a whole do not integrate the judicial exception into a practical application.
The additional elements, “applied to a communication system, wherein the communication system comprises a terminal and a server,” “by the terminal,” and “by the server” are implementing an abstract idea on a computer, or merely uses a computer as a tool to perform/apply an abstract idea. It invokes a generic computer merely as a tool to perform the judicial exception or an existing process by using of a computer or other machinery in its ordinary capacity. (i.e., “apply it”, MPEP 2106.05(f)).
The additional elements, “sending, by the terminal, user behavior information of a user to the server,” are merely data gathering recited at a high level of generality and insignificant extra-solution activity (pre-solution activity) (MPEP 2106.05 (g)).
The additional elements, “target article” and “recommendation” are generally linking the use of the judicial exception to a particular technological environment or field of use (e.g., web article recommendation) (MPEP 2106.05(h)).
When considered a whole, the claimed invention fails to recite any improvement in any technology or technical field (MPEP 2106.05(a)) or recite any meaningful limitations (MPEP 2106.05(e)). The limitations are no more than mere automation of determining a user’s interest and providing a recommended article along with a reason for the recommendation using a generic computer as a tool. Specifically, a marketing personnel can collect behavior information of a user, identify the user’s interest in articles, and present a recommended article and a reason for the recommendation to the user. Upon the user accepting/selecting the recommended article, the marketing personnel can further present the full article and detailed recommendation information (statistics of the user’s interests) to the user.
Further, although ¶ [0003] of the specification of the instant application recites “inaccurate messages pushed to a user may cause antipathy of the user and reduce user experience,” however improving a user’s experience while using a computer (e.g., a terminal and a server) is not, without more, sufficient to render the claims directed to an improvement in computer functionality. The claim focuses on solving a business problem using generic computer technology as a tool, rather than on improving computer capabilities. Providing an article and other recommendation information based on a user’s behavior are longstanding methods of human activity. Improvement, directed to determining what recommended/targeted information is presented/displayed to a user, is an improvement to the abstract idea itself and is not an improvement to the functioning of the computer itself or any other technology or technical field.
Even when considered in combination, these additional elements do no more than automate marketing/advertising/business relations and/or personal behavior/relationships that a business personnel used to perform using the computer components as a tool. Therefore, the additional elements represent mere instructions to apply a judicial exception/abstract idea, which do not integrate the judicial exception into a practical application.
Step 2B: the claim does not recite additional elements that are sufficient to amount to significantly more than the abstract idea when considered both individually and as a whole.
under Step 2B, besides the additional elements already analyzed under MPEP 2106.05(f), 2106.05(g), and 2106.05(h) (the same analysis as that of Step 2B, Prong 2), additional element(s)/limitation(s) that are insignificant extra-solution activity (MPEP 2106.05(g)) in step 2A, Prong 2, are re-evaluated in Step 2B as the following to determine whether the additional element(s)/limitation(s) are well-understood, routine, conventional activities.
Specifically, the claim limitations, “sending, by the terminal, user behavior information of a user to the server,” are merely receiving or transmitting data over a network, which are mere judicial-recognized well-understood, routine, conventional activity, and remains insignificant extra-solution activity even upon reconsideration. (MPEP 2106.05(d)(II)).
When considered as a whole, these additional elements represent mere instructions to apply a judicial exception and insignificant extra-solution activities, which do not provide an inventive concept, and, in other words, amount to significantly more.
Therefore, independent claim 15 is not eligible.
Independent claims 1 and 19 recite similar claim limitations as claim 15. Compared to claim 15, claim 19 recites additional limitations, “A terminal, comprising: one or more processors; and a memory, storing code, wherein when the code is executed by the one or more processors, the terminal is enabled to perform operations.” However, these limitations are additional elements directed to implementing an abstract idea on a computer, or merely uses a computer as a tool to perform/apply an abstract idea. It invokes a generic computer merely as a tool to perform the judicial exception or an existing process by using of a computer or other machinery in its ordinary capacity. (i.e., “apply it”, MPEP 2106.05(f)). Therefore, independent claims 1 and 19 are not eligible.
Dependent claims 2-7, 14, 16-18, and 20 fail to recite additional elements that could integrate the judicial exception into a practical application or amount to significantly more than the abstract idea. Specifically:
Dependent claims 2, 16, and 20 recite an abstract idea directed to Certain Methods of Organizing Human Activity: “obtaining a display template corresponding to the first data, or obtaining a display template corresponding to the second data; and wherein displaying the second interface comprises: displaying the second interface, wherein the content of the target article and the recommendation information that corresponds to the second data and that is displayed by using the display template corresponding to the second data are displayed on the second interface.” Moreover, claims 2, 16, and 20 recite an abstract idea directed to Mental Processes: “obtaining a display template corresponding to the first data based on the first data, or obtaining a display template corresponding to the second data based on the second data” (The claimed “obtaining” is interpreted as “determining.”).
Dependent claim 3 recites an abstract idea directed to Certain Methods of Organizing Human Activity and Mental Processes: “wherein obtaining the display template corresponding to the first data or obtaining the display template corresponding to the second data comprises: obtaining the display template corresponding to the first data or the display template corresponding to the second data based on the recommendation reason field.” (The claimed “obtaining” is interpreted as “determining.”).
Dependent claims 4 and 17 recites an abstract idea directed to Certain Methods of Organizing Human Activity: “wherein second content is further displayed on the second interface, and the second content is obtained based on the related data of the category to which the target article belongs.”
Moreover, claims 4 and 17 recite additional elements: “wherein before displaying the second interface, the method further comprises: receiving related data that is of a category to which the target article belongs and that is pushed by the server.” These additional elements are directed to insignificant extra-solution activity (pre-solution activity) (MPEP 2106.05 (g)) and judicial-recognized well-understood, routine, conventional activity (receiving or transmitting data over a network, MPEP 2106.05(d)(II)).
Dependent claims 5 and 18 recite additional elements: “wherein the user behavior information comprises any one of the following: geographical location information, subscription dynamic category information, social dynamic category information, or user interest category information.” These additional elements directed to linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)).
Dependent claim 6 recites additional elements: “wherein the user behavior information comprises the user interest category information; and wherein: the target article is determined by the server based on the user interest category information, and the first data is related to the user interest category information; or the first data is related to the target article information and the interest category information.” These additional elements directed to linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)).
Dependent claim 7 recites additional elements: “wherein the second data displayed on the second interface comprises: a ranking list of user interests.” These additional elements directed to linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)).
Dependent claim 14 recites an abstract idea directed to Mathematical Concepts (mathematical relationships; mathematical formulas or equations; mathematical calculations): “the user interest category information comprises an interest vector weight of each article category, and the interest vector weight of each article category indicates a preference degree of the user for each category of articles … determining the interest vector weight of each article category based on the article categories of the n historical articles and a tap frequency, a time attenuation factor, and a weight of each article category” (see the mathematical concept in ¶ [0146] of the specification of the instant application). Moreover, claim 14 recites an abstract idea directed to Certain Methods of Organizing Human Activity: “wherein before sending the user behavior information of the user, the method further comprises: obtaining n historical articles browsed by the user, wherein n is a positive integer greater than 1; extracting article categories of the n historical articles browsed by the user; and determining the interest vector weight of each article category based on the article categories of the n historical articles and a tap frequency, a time attenuation factor, and a weight of each article category.” Claim 14 recites an abstract idea directed to Mental Processes: “wherein before sending the user behavior information of the user, the method further comprises: obtaining n historical articles browsed by the user, wherein n is a positive integer greater than 1; extracting article categories of the n historical articles browsed by the user; and determining the interest vector weight of each article category based on the article categories of the n historical articles and a tap frequency, a time attenuation factor, and a weight of each article category” (The claimed “obtaining” is interpreted as “determining.” The calculation is simply enough to be practically performed by the human mind). Further, claim 14 recites additional elements: “wherein the user behavior information comprises the user interest category information.” These additional elements directed to linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)).
Therefore, dependent claims 2-7, 14, 16-18, and 20 are not eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bitran (US 2017/0039327 A1), in view of Moon (US 2013/0132401 A1), hereinafter Bitran-Moon.
Per claims 1 and 19, Bitran teaches “A terminal, (Fig.1; ¶ [0021], computing system 10 includes a client computing device 12, which, for example, may take the form of a smart phone or tablet computing device) comprising: one or more processors; and a memory, storing code, wherein when the code is executed by the processor, (Fig. 14; ¶ [0003], a client computing device comprises a processor and an electronic personal assistant application program executable by the processor; ¶ [0111], volatile memory 1403, and a non-volatile storage device 1404) the terminal is enabled to perform operations comprising: sending user behavior information of a user to a server; (Fig.1; ¶ [0022-0024], Client computing device 12 is configured to execute an electronic personal assistant application program 24 … the electronic personal assistant program is configured to passively monitor various user data 26 on the client computing device 12 and other client computing devices 16, such as location data, search history, download history, browsing history, contacts, social network data, calendar data, biometric data, medical device data, purchase history, etc. In some examples, user data 26 may be generated by or otherwise associated with user activities across a plurality of programs … User data 26 is transmitted from the electronic personal assistant application program 24 to the personal assistant user data interpretation engine 28 executed on server system 14; ¶ [0099], the suggestion engine 74 may learn behaviors of the user by analyzing the user's behavior over time) obtaining a first message sent by the server, wherein the first message comprises target article information and first data, the first data comprises a recommendation reason field, the target article information is determined by the server based on the user behavior information, and the first data is related to the target article information and the user behavior information; displaying a first interface, wherein the first interface comprises a first recommendation, the first recommendation comprises first content and recommendation information corresponding to the first data, and the first content is obtained based on the target article information; (Fig. 7, a push notification/article 710 and a recommendation information/reason 720 (corresponding to the claimed first data): “Here is a local event for your favorite workout activity that fits your fitness level. Your weekend is free.”; Fig. 9, a push notification/article 910 and a recommendation information/reason: “Here is some news about one of your favorite workout activities.” Fig.10, a push notification/article 1010/1020 and a recommendation information/reason: “People who suffer from similar conditions like you read these.” Fig.11, a push notification/article 1110/1120/1130/1140 and a recommendation information/reason: “Consider the following insights regarding health advisories”; ¶ [0092-0094], the personal assistant user data interpretation engine 28 may infer from calendar data that in one month the user is traveling to India for a three-month visit. The suggestion engine 74 may identify a vaccine alert for India in the alerts 60 … A notification agent 64 within server system 14 may instruct the alert notification engine 68 of the electronic personal assistant application server 66 to send a message 70 in the form of a push notification featuring the content of the India vaccine alert 60 to the electronic personal assistant application program 24 executed on the client device 12 … the alert notification engine 68 may transmit to the electronic personal assistant application program 24 a link 1110 to the identified alert regarding India vaccines. The client computing device 12 may then display the link 1110 in the GUI 510 … personal assistant application program 24 may generate for the user and display a customized title 1120 for the alert that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. In this example, the customized title 1110 makes reference to the user's upcoming trip to India, to thereby make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert; ¶ [0081-0083], With reference now to FIG. 9 and in another example, the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article in which the user may be interested … The suggestion engine 74 may identify a news article that contains content about an amateur golfer. Based on the user's golfing ability, the personal assistant user data interpretation engine 28 may infer that the user may enjoy reading the article. Accordingly, the suggestion engine 74 may transmit to the electronic personal assistant application program 24 a link 910 to the identified news article for display in the GUI 510; ¶ [0084-0085], With reference now to FIG. 10 and in another example, the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article, publication or other digital content in which the user may be interested … In the course of such searching the suggestion engine 74 may determine that the user suffers from migraine headaches ... the suggestion engine 74 may identify two articles related to migraine headaches. Accordingly, the suggestion engine 74 may transmit to the electronic personal assistant application program 24 two links 1010 and 1020 to the identified articles for display in the GUI 510; ¶ [0088], the suggestion engine 74 may locate the article indicated by link 1010 that suggests that migraine intensity can be reduced by ingesting bananas. The suggestion engine 74 may also analyze the current location of the user to determine that the user is at home. The suggestion engine may further determine from the user's purchasing history in the user personal assistant knowledge base 30 that the user regularly purchases bananas. Accordingly, the suggestion engine 74 may correlate information gleaned from the migraine-related article with the user biometric data, and in some examples the current location of the user, to determine that providing the health-related suggestion of the article to the user may help the user quickly address and perhaps alleviate the migraine headache. In response to such correlation, the suggestion engine may transmit to the electronic personal assistant application program 24 the link 1010 to the identified article discussing possibly reducing migraine intensity with bananas. The client computing device 12 may then display the link 1010 in the GUI 510; ¶ [0074], The suggestion engine 74 also may analyze calendar data of the user to determine that the user is available during the time and date of the bike ride event 710. Based on the user's calendar data, the user's location, the user's preference for bike riding, and the user's fitness level, the suggestion engine 74 may provide a health-related suggestion in the form of the bike ride event 710 to the electronic personal assistant application program 24 for display in the GUI 510. In some examples the electronic personal assistant application program 24 may generate for the user and display a customized title 720 for the event that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. The customized title 720 may communicate that the event relates to the user's favorite workout activity, fits the user's fitness level, and that the user is available for the event; also see ¶¶ [0068-0074] regarding Fig.7, ¶¶ [0081-0083] regarding Fig.9, ¶¶ [0084-0090] regrading Fig.10, ¶¶ [0091-0099] regarding Fig.11) receiving a first operation on the first recommendation;” (¶ [0094], make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert).
However, Bitran does not explicitly disclose the claim limitations regarding after clicking the recommendation (pushed recommendation/notification of an article), “sending a first request to the server in response to the first operation, wherein the first request comprises an identifier of the first message, the first request requests the server to obtain content of a target article and second data based on the identifier of the first message, and the second data is related to the first data; obtaining the content of the target article and the second data from the server; and displaying a second interface, wherein the content of the target article and recommendation information corresponding to the second data are displayed on the second interface.”
Moon teaches “sending a first request to the server in response to the first operation, wherein the first request comprises an identifier of the first message, the first request requests the server to obtain content of a target article and second data based on the identifier of the first message, and the second data is related to the first data; obtaining the content of the target article and the second data from the server; and displaying a second interface, wherein the content of the target article and recommendation information corresponding to the second data are displayed on the second interface.” (Figs.1, 2, 3; ¶ [0035-0036], each news result includes, at least, a title 204 and an abstract 206. Title 204 provides a short description of the content of the news article, and the abstract 206 provides a synopsis of the content of the news article. Once the user clicks on a news article, the Internet browser accesses the referenced webpage to present the news article. In one embodiment, the textual content of the news article is referred to herein as the body of the news article. In other embodiments, the news article include one or more of a title, a body, a summary, one or more pictures, a video clip, user comments, statistical information about the page, etc. On the right side of the page, an advertising area includes a list of advertisements, which are sometimes related to the topic of the search; ¶ [0038-0040], FIG. 3 shows a news article with links to related content, according to one embodiment. A typical news article includes, at least, a title 304 and a body 306. The title 304 provides a headline for the article, and the body 306 includes a textual description of the news article. In some cases, the news article may include one or more pictures, and one or more multimedia segments. Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy …; ¶ [0049], Given a seed article s, the goal of the method to generate post-click news recommendation is to identify a set of candidate article; also see ¶ [0028] for server-terminal relationship). [Comment: The reference to the first message for the title of the article is the identifier of the first message. The related content section 302 (corresponding to second data) is related to the topic/reason of the article (corresponding to the first data).]
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine post-click operations including displaying a target article and recommendation information of Moon into displaying a recommendation of a target article and a recommendation reason of Bitran, such that a recommendation of a target article and a recommendation reason for the article would be displayed and, after clicking the recommendation, the article and another recommendation information related to the recommendation topic/reason would be displayed. One of ordinary skill in the art would have been motivated to do so because Bitran recognizes that it would have been advantageous to provide post-click recommendation information along with a target article (¶ [0005-0006], Recommending interesting news articles to users has become extremely important for internet providers looking to maintain users' interest … methods to engage users after their initial visit is largely under explored … This process is referred to herein as post-click news recommendation, which has the goal of promoting users' navigation to other web pages … Therefore, an effective post-click news recommendation is critical to online news websites). (KSR(G), TSM, MPEP 2143). Additionally, one of ordinary skill in the art would have been motivated to do so because this is combining prior art elements according to known methods to yield predictable results, specifically, combining known methods of recommendation for articles to yield predictable results (KSR(A), MPEP 2143).
Per claim 15, Bitran teaches “A method, applied to a communication system, wherein the communication system comprises a terminal and a server, (Fig.1; ¶ [0021], computing system 10 includes a client computing device 12, which, for example, may take the form of a smart phone or tablet computing device, configured to communicate via a computer network with a server system 14) and the method comprises: sending, by the terminal, user behavior information of a user to the server; (Fig.1; ¶ [0022-0024], Client computing device 12 is configured to execute an electronic personal assistant application program 24 … the electronic personal assistant program is configured to passively monitor various user data 26 on the client computing device 12 and other client computing devices 16, such as location data, search history, download history, browsing history, contacts, social network data, calendar data, biometric data, medical device data, purchase history, etc. In some examples, user data 26 may be generated by or otherwise associated with user activities across a plurality of programs … User data 26 is transmitted from the electronic personal assistant application program 24 to the personal assistant user data interpretation engine 28 executed on server system 14; ¶ [0099], the suggestion engine 74 may learn behaviors of the user by analyzing the user's behavior over time) determining, by the server based on the user behavior information, target article information and first data corresponding to the target article information, wherein the first data comprises a recommendation reason field, and the first data is related to the target article information and the user behavior information; generating, by the server, a first message based on the target article information and the first data; receiving, by the terminal, the first message sent by the server, wherein the first message comprises the target article information and the first data; displaying, by the terminal, a first interface, wherein the first interface comprises a first recommendation, the first recommendation comprises first content and recommendation information corresponding to the first data, and the first content is obtained based on the target article information; (Fig. 7, a push notification/article 710 and a recommendation information/reason 720 (corresponding to the claimed first data): “Here is a local event for your favorite workout activity that fits your fitness level. Your weekend is free.”; Fig. 9, a push notification/article 910 and a recommendation information/reason: “Here is some news about one of your favorite workout activities.” Fig.10, a push notification/article 1010/1020 and a recommendation information/reason: “People who suffer from similar conditions like you read these.” Fig.11, a push notification/article 1110/1120/1130/1140 and a recommendation information/reason: “Consider the following insights regarding health advisories”; ¶ [0092-0094], the personal assistant user data interpretation engine 28 may infer from calendar data that in one month the user is traveling to India for a three-month visit. The suggestion engine 74 may identify a vaccine alert for India in the alerts 60 … A notification agent 64 within server system 14 may instruct the alert notification engine 68 of the electronic personal assistant application server 66 to send a message 70 in the form of a push notification featuring the content of the India vaccine alert 60 to the electronic personal assistant application program 24 executed on the client device 12 … the alert notification engine 68 may transmit to the electronic personal assistant application program 24 a link 1110 to the identified alert regarding India vaccines. The client computing device 12 may then display the link 1110 in the GUI 510 … personal assistant application program 24 may generate for the user and display a customized title 1120 for the alert that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. In this example, the customized title 1110 makes reference to the user's upcoming trip to India, to thereby make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert; ¶ [0081-0083], With reference now to FIG. 9 and in another example, the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article in which the user may be interested … The suggestion engine 74 may identify a news article that contains content about an amateur golfer. Based on the user's golfing ability, the personal assistant user data interpretation engine 28 may infer that the user may enjoy reading the article. Accordingly, the suggestion engine 74 may transmit to the electronic personal assistant application program 24 a link 910 to the identified news article for display in the GUI 510; ¶ [0084-0085], With reference now to FIG. 10 and in another example, the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article, publication or other digital content in which the user may be interested … In the course of such searching the suggestion engine 74 may determine that the user suffers from migraine headaches ... the suggestion engine 74 may identify two articles related to migraine headaches. Accordingly, the suggestion engine 74 may transmit to the electronic personal assistant application program 24 two links 1010 and 1020 to the identified articles for display in the GUI 510; ¶ [0088], the suggestion engine 74 may locate the article indicated by link 1010 that suggests that migraine intensity can be reduced by ingesting bananas. The suggestion engine 74 may also analyze the current location of the user to determine that the user is at home. The suggestion engine may further determine from the user's purchasing history in the user personal assistant knowledge base 30 that the user regularly purchases bananas. Accordingly, the suggestion engine 74 may correlate information gleaned from the migraine-related article with the user biometric data, and in some examples the current location of the user, to determine that providing the health-related suggestion of the article to the user may help the user quickly address and perhaps alleviate the migraine headache. In response to such correlation, the suggestion engine may transmit to the electronic personal assistant application program 24 the link 1010 to the identified article discussing possibly reducing migraine intensity with bananas. The client computing device 12 may then display the link 1010 in the GUI 510; ¶ [0074], The suggestion engine 74 also may analyze calendar data of the user to determine that the user is available during the time and date of the bike ride event 710. Based on the user's calendar data, the user's location, the user's preference for bike riding, and the user's fitness level, the suggestion engine 74 may provide a health-related suggestion in the form of the bike ride event 710 to the electronic personal assistant application program 24 for display in the GUI 510. In some examples the electronic personal assistant application program 24 may generate for the user and display a customized title 720 for the event that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. The customized title 720 may communicate that the event relates to the user's favorite workout activity, fits the user's fitness level, and that the user is available for the event; also see ¶¶ [0068-0074] regarding Fig.7, ¶¶ [0081-0083] regarding Fig.9, ¶¶ [0084-0090] regrading Fig.10, ¶¶ [0091-0099] regarding Fig.11) receiving, by the terminal, a first operation on the first recommendation;” (¶ [0094], make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert).
However, Bitran does not explicitly disclose the claim limitations regarding after clicking the recommendation (pushed recommendation/notification of an article), “sending, by the terminal, a first request to the server in response to the first operation, wherein the first request comprises an identifier of the first message, the first request requests the server to obtain content of a target article and second data based on the identifier of the first message, and the second data is related to the first data; obtaining, by the server, the content of the target article and the second data based on the first request; sending, by the server, the content of the target article and the second data to the terminal; receiving, by the terminal, the content of the target article and the second data that are sent by the server; and displaying, by the terminal, a second interface, wherein the content of the target article and recommendation information corresponding to the second data are displayed on the second interface”
Moon teaches “sending, by the terminal, a first request to the server in response to the first operation, wherein the first request comprises an identifier of the first message, the first request requests the server to obtain content of a target article and second data based on the identifier of the first message, and the second data is related to the first data; obtaining, by the server, the content of the target article and the second data based on the first request; sending, by the server, the content of the target article and the second data to the terminal; receiving, by the terminal, the content of the target article and the second data that are sent by the server; and displaying, by the terminal, a second interface, wherein the content of the target article and recommendation information corresponding to the second data are displayed on the second interface” (Figs.1, 2, 3; ¶ [0035-0036], each news result includes, at least, a title 204 and an abstract 206. Title 204 provides a short description of the content of the news article, and the abstract 206 provides a synopsis of the content of the news article. Once the user clicks on a news article, the Internet browser accesses the referenced webpage to present the news article. In one embodiment, the textual content of the news article is referred to herein as the body of the news article. In other embodiments, the news article include one or more of a title, a body, a summary, one or more pictures, a video clip, user comments, statistical information about the page, etc. On the right side of the page, an advertising area includes a list of advertisements, which are sometimes related to the topic of the search; ¶ [0038-0040], FIG. 3 shows a news article with links to related content, according to one embodiment. A typical news article includes, at least, a title 304 and a body 306. The title 304 provides a headline for the article, and the body 306 includes a textual description of the news article. In some cases, the news article may include one or more pictures, and one or more multimedia segments. Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy …; ¶ [0049], Given a seed article s, the goal of the method to generate post-click news recommendation is to identify a set of candidate article; also see ¶ [0028] for server-terminal relationship). [Comment: The reference to the first message for the title of the article is the identifier of the first message. The related content section 302 (corresponding to second data) is related to the topic/reason of the article (corresponding to the first data).]
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine post-click operations including displaying a target article and recommendation information of Moon into displaying a recommendation of a target article and a recommendation reason of Bitran, such that a recommendation of a target article and a recommendation reason for the article would be displayed and, after clicking the recommendation, the article and another recommendation information related to the recommendation topic/reason would be displayed. One of ordinary skill in the art would have been motivated to do so because Bitran recognizes that it would have been advantageous to provide post-click recommendation information along with a target article (¶ [0005-0006], Recommending interesting news articles to users has become extremely important for internet providers looking to maintain users' interest … methods to engage users after their initial visit is largely under explored … This process is referred to herein as post-click news recommendation, which has the goal of promoting users' navigation to other web pages … Therefore, an effective post-click news recommendation is critical to online news websites). (KSR(G), TSM, MPEP 2143). Additionally, one of ordinary skill in the art would have been motivated to do so because this is combining prior art elements according to known methods to yield predictable results, specifically, combining known methods of recommendation for articles to yield predictable results (KSR(A), MPEP 2143).
Per claims 2, 16, and 20, Bitran further teaches “wherein when the code is executed by the one or more processors, the terminal is enabled to perform operations further comprising: (Fig. 14; ¶ [0003], a client computing device comprises a processor and an electronic personal assistant application program executable by the processor; ¶ [0111], volatile memory 1403, and a non-volatile storage device 1404) obtaining a display template corresponding to the first data based on the first data.” (Figs. 7, 9, 10, 11 show a template of a pushed notification/article (e.g., 710) and a recommendation information/reason (e.g., 720)).
Moon further teaches “obtaining a display template corresponding to the first data, (Fig.2; [0035-0036], each news result includes, at least, a title 204 and an abstract 206. Title 204 provides a short description of the content of the news article, and the abstract 206 provides a synopsis of the content of the news article…) or obtaining a display template corresponding to the second data; and wherein displaying the second interface comprises: displaying the second interface, wherein the content of the target article and the recommendation information that corresponds to the second data and that is displayed by using the display template corresponding to the second data are displayed on the second interface” (Fig.3., ¶ [0036], Once the user clicks on a news article, the Internet browser accesses the referenced webpage to present the news article. In one embodiment, the textual content of the news article is referred to herein as the body of the news article. In other embodiments, the news article include one or more of a title, a body, a summary, one or more pictures, a video clip, user comments, statistical information about the page, etc. On the right side of the page, an advertising area includes a list of advertisements, which are sometimes related to the topic of the search; ¶ [0038-0039], FIG. 3 shows a news article with links to related content, according to one embodiment. A typical news article includes, at least, a title 304 and a body 306. The title 304 provides a headline for the article, and the body 306 includes a textual description of the news article. In some cases, the news article may include one or more pictures, and one or more multimedia segments. Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy). [Comment: the combination/motivation is the same as that of independent claims.]
Per claim 3, Bitran further teaches “wherein obtaining the display template corresponding to the first data, or obtaining the display template corresponding to the second data comprises: obtaining the display template corresponding to the first data or the display template corresponding to the second data based on the recommendation reason field” (Fig. 7, a push notification/article 720 and a recommendation information/reason 720 (corresponding to the claimed first data): “Here is a local event for your favorite workout activity that fits your fitness level. Your weekend is free.”; Fig. 9, a push notification/article 910 and a recommendation information/reason: “Here is some news about one of your favorite workout activities.” Fig.10, a push notification/article 1010/1020 and a recommendation information/reason: “People who suffer from similar conditions like you read these.” Fig.11, a push notification/article 1110/1120/1130/1140 and a recommendation information/reason: “Consider the following insights regarding health advisories”; ¶ [0094], the customized title 1110 makes reference to the user's upcoming trip to India, to thereby make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert; ¶ [0074], The customized title 720 may communicate that the event relates to the user's favorite workout activity, fits the user's fitness level, and that the user is available for the event).
Moon further teaches “wherein obtaining the display template corresponding to the first data, or obtaining the display template corresponding to the second data comprises: obtaining the display template corresponding to the first data or the display template corresponding to the second data based on the recommendation reason field” (Figs 2, 3; ¶ [0038-0039], FIG. 3 shows a news article with links to related content … Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy; also see ¶ [0035-0036]). [Comment: the combination/motivation is the same as that of independent claims.]
Per claims 4 and 17, Bitran further teaches “wherein before displaying, by the terminal, the second interface, the method further comprises: receiving, by the terminal, related data that is of a category to which the target article belongs and that is pushed by the server” (Fig. 7, a push notification/article 720 and a recommendation information/reason 720 (corresponding to the claimed first data): “Here is a local event for your favorite workout activity that fits your fitness level. Your weekend is free.”; Fig. 9, a push notification/article 910 and a recommendation information/reason: “Here is some news about one of your favorite workout activities.” Fig.10, a push notification/article 1010/1020 and a recommendation information/reason: “People who suffer from similar conditions like you read these.” Fig.11, a push notification/article 1110/1120/1130/1140 and a recommendation information/reason: “Consider the following insights regarding health advisories”; ¶ [0094], the customized title 1110 makes reference to the user's upcoming trip to India, to thereby make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert; ¶ [0074], The customized title 720 may communicate that the event relates to the user's favorite workout activity, fits the user's fitness level, and that the user is available for the event).
Moon further teaches “wherein before displaying, by the terminal, the second interface, the method further comprises: receiving, by the terminal, related data that is of a category to which the target article belongs and that is pushed by the server, wherein second content is further displayed on the second interface, and the second content is obtained based on the related data of the category to which the target article belongs” (Fig.3; ¶ [0039-0040], Embodiments of the invention provide a related content section 302, which includes one or more links to related news articles. What makes a news article related to the current news article? First of all, two news articles should be contextually similar to each other. In this sense, similarity or relevance is an important indicator of relatedness … For a related article to be recommended, the related article should cover only a fraction of the content of the article be read, and include other content that is novel and news-worthy … In addition to the notions of similarity and novelty, two new factors for measuring relatedness are introduced below: connection clarity and transition smoothness; ¶ [0042], To find related news articles, there should be a clear connection between two documents to maintain topical continuity. In other words, the overlap between two documents should be comprised of some meaningful topical context; ¶ [0062], in order to make two documents related, the documents should share a clear story thread that makes them topically cohesive. This can often be achieved by repeating the same topic, or a similar topic, which forms topical links that connect two documents together and make them related.) [Comment: the combination/motivation is the same as that of independent claims.]
Per claims 5 and 18, Bitran further teaches “wherein the user behavior information comprises any one of the following: geographical location information, (¶ [0023], Specific examples of these various types of user data 26 will now be described. Location data may include for example, GPS coordinate data (latitude and longitude) obtained by a GPS receiver implemented on any client computing device, an identifier such as an IP address and/or Wi-Fi access point identifier that can be resolved to a generalized geographic location, a user check-in at a location via a social network program, etc; ¶ [0091-0093], With reference now to FIG. 11 and in another example, the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of health advisories that relate … geographic travel history of the user … the personal assistant user data interpretation engine 28 may infer from calendar data that in one month the user is traveling to India for a three-month visit … the alert may be targeted to users who the data interpretation engine 28 infers will soon travel to India, such as the user in the present example) subscription dynamic category information, social dynamic category information, (¶ [0023], The social network data may include a user's friends list, a list of social network entities “liked” by the user, check-ins made by the user at locations via a social network program, posts written by the user, etc.) or user interest category information” (¶ [0023], Specific examples of these various types of user data 26 will now be described … Each of these applications and files may have metadata associated with them, such as categories, genres, etc; ¶ [0068], a proactive push notification of a fitness event in which the user may be interested. In some examples the suggestion engine 74 may perform searches in one or more of the user personal assistant knowledge base 30 …; ¶ [0071], The personal assistant user data interpretation engine 28 may infer from the user's profile 32 that the user enjoys bike riding and has, for example, performed bike rides in the last month of 25, 30 and 40 miles … matches the user's fitness level; ¶ [0082], the suggestion engine 74 may determine from data in the user's profile 32 that the user has a preference for playing golf and that the user has a golf handicap of 7, which corresponds to a numerical measure of a golfer's playing ability … he suggestion engine 74 may search news aggregators and other online content sources for articles and other publications that would be of interest to a person having the user's golfing playing ability (i.e., an amateur golfer having a single-digit handicap); ¶ [0084], the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article, publication or other digital content in which the user may be interested).
Per claim 6, Bitran further teaches “wherein the user behavior information comprises the user interest category information; and wherein: the target article is determined by the server based on the user interest category information, and the first data is related to the interest category information; or the first data is related to the user target article information and the interest category information” (Figs. 7, 9, 10, and 11; ¶ [0074], The suggestion engine 74 also may analyze calendar data of the user to determine that the user is available during the time and date of the bike ride event 710. Based on the user's calendar data, the user's location, the user's preference for bike riding, and the user's fitness level, the suggestion engine 74 may provide a health-related suggestion in the form of the bike ride event 710 to the electronic personal assistant application program 24 for display in the GUI 510. In some examples the electronic personal assistant application program 24 may generate for the user and display a customized title 720 for the event that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. The customized title 720 may communicate that the event relates to the user's favorite workout activity, fits the user's fitness level, and that the user is available for the event; ¶ [0083], The suggestion engine 74 may identify a news article that contains content about an amateur golfer. Based on the user's golfing ability, the personal assistant user data interpretation engine 28 may infer that the user may enjoy reading the article. Accordingly, the suggestion engine 74 may transmit to the electronic personal assistant application program 24 a link 910 to the identified news article for display in the GUI 510; ¶ [0088], the suggestion engine 74 may correlate information gleaned from the migraine-related article with the user biometric data, and in some examples the current location of the user, to determine that providing the health-related suggestion of the article to the user may help the user quickly address and perhaps alleviate the migraine headache …; ¶ [0093-0094], the alert may be targeted to users who the data interpretation engine 28 infers will soon travel to India, such as the user in the present example. Accordingly, the alert notification engine 68 may transmit to the electronic personal assistant application program 24 a link 1110 to the identified alert regarding India vaccines. The client computing device 12 may then display the link 1110 in the GUI 510. In one example, personal assistant application program 24 may generate for the user and display a customized title 1120 for the alert that is based on data received from the suggestion engine 74 and/or other data from the user personal assistant knowledge base 30. In this example, the customized title 1110 makes reference to the user's upcoming trip to India, to thereby make the article more relevant to the user and increase the chances of the user clicking on the link 1110 to the alert).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Bitran-Moon, in view of Immonen (US 2014/0059647 A1).
Per claim 7, Bitran-Moon does not teach “wherein the second data displayed on the second interface comprises: a ranking list of user interests.”
Immonen teaches displaying, on a user interface, a ranking/top list of a user’ interests based on monitoring behavior of the user to provide content interested by the user (Fig.5C; ¶ [0110-0112], The interests have been categorized into multiple categories such as Alcohol&Tobacco, Cars, Travel and Sports … This view 504 especially illustrates how the user may conveniently go into details of a higher level category, such as ‘Alcohol & Tobacco’ … FIG. 5 c is one more example of a browser-based UI and related view. The shown view 506 discloses statistical data such as ‘Top categories’ or ‘Interest graph’. The arrangement may be configured to create such data indicative of user interests based on at least one tracked element selected from the group consisting of: search term, keyword, web site (visited, input or otherwise indicated), web page, web page category, web site category, message header, message topic, and message payload; claim 1, wherein the personal media profile describes the user's interests … wherein the interests are represented on a number of levels including interest categories and further wherein the interests are at least partially determined based on monitoring the user behavior relative to the network; ¶ [0028-0029], establishing a user-adjustable personal media profile for a web user capable of accessing a network … wherein the interests are represented on a number of levels including interest categories, such as automotive or travel categories, and further wherein the interests are at least partially determined based on monitoring the user behavior relative to the network … wherein the user is provided with notifications indicative of content suggestions conforming to the personal media profile).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine displaying a ranking list of interests of Immonen into displaying a target article along with information related to a user’s interest(s) of Bitran-Moon, such that a target article along with a ranking list of a user’s interests would be displayed. One of ordinary skill in the art would have been motivated to do so because Immonen recognizes that it would have been advantageous to display a ranking list of interests for a user to access and control/alter the list to provide content interested by the user (¶ [0011], wherein the user is provided with a number of notifications indicative of content suggestions conforming to the personal media profile via the terminal, and wherein personal media profile data is selectively, preferably user-controllably; ¶ [0110-0111], The shown view 502 visualizes few controls for managing profile details such as adjusting interests information. The interests have been categorized into multiple categories such as Alcohol&Tobacco, Cars, Travel and Sports. The user is provided via the UI a possibility to alter the current profile … This view 504 especially illustrates how the user may conveniently go into details of a higher level category, such as ‘Alcohol & Tobacco’, and within the category independently set off/on, i.e. block/allow, lower level items such as brand names or item types … ) (KSR(G), TSM, MPEP 2143). Additionally, one of ordinary skill in the art would have been motivated to do so because this is combining prior art elements according to known methods to yield predictable results, specifically, combining known methods of displaying user interest-related information to yield predictable results, especially given that Bitran, Moon, and Immonen are in the same field of endeavor of providing content interested by a user (KSR(A), MPEP 2143).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Bitran-Moon, in view of Dolan (US 2012/0290522 A1).
Per claim 14, Bitran further teaches “wherein the user behavior information comprises the user interest category information” (¶ [0023], Specific examples of these various types of user data 26 will now be described … Each of these applications and files may have metadata associated with them, such as categories, genres, etc; ¶ [0068], a proactive push notification of a fitness event in which the user may be interested. In some examples the suggestion engine 74 may perform searches in one or more of the user personal assistant knowledge base 30 …; ¶ [0071], The personal assistant user data interpretation engine 28 may infer from the user's profile 32 that the user enjoys bike riding and has, for example, performed bike rides in the last month of 25, 30 and 40 miles … matches the user's fitness level; ¶ [0082], the suggestion engine 74 may determine from data in the user's profile 32 that the user has a preference for playing golf and that the user has a golf handicap of 7, which corresponds to a numerical measure of a golfer's playing ability … he suggestion engine 74 may search news aggregators and other online content sources for articles and other publications that would be of interest to a person having the user's golfing playing ability (i.e., an amateur golfer having a single-digit handicap); ¶ [0084], the electronic personal assistant application program 24 may provide a health-related suggestion in the form of a proactive push notification of a news article, publication or other digital content in which the user may be interested).
Moon further teaches “wherein the user behavior information comprises the user interest category information, the user interest category information comprises an interest vector weight of each article category, and the interest vector weight of each article category indicates a preference degree of the user for each category of articles” (Abstract, providing internet content, such as related news articles … scores are calculated for relevance, novelty, connection clarity, and transition smoothness … the score for transition smoothness measures the interest in reading each candidate; ¶ [0098], a plurality of candidates is defined based on the seed, such as a news article that has been selected by the user. Further, in operation 1004, scores are calculated for each candidate for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on the relevance score of an intersection between the seed and each candidate, and the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate; ¶ [0079], Such a document-based context is represented as a vector of documents … The relevance score of document di with respect to “query” (s−d) is g(s−d, di). In one embodiment, the BM25 retrieval function is used to compute relevance scores. This implies that if a document is more relevant to (s−d), the document would play a more important role to determine the context of (s−d). Similarly, the context vector {right arrow over (C)}d−s is estimated for (d−s). In one embodiment, the transition smoothness score is computed using the cosine similarity between context vectors as follows … ; ¶ [0062-0063], in order to make two documents related, the documents should share a clear story thread that makes them topically cohesive. This can often be achieved by repeating the same topic, or a similar topic, which forms topical links that connect two documents together and make them related … the clearer the topical connection is, the more related the two documents will probably be … topics associated with each document are identified using probabilistic topic models). [Comment: the combination/motivation is the same as that of independent claims.]
However, Bitran-Moon does not teach “wherein before sending the user behavior information of the user (e.g., a user’s interests), the method further comprises: obtaining n historical articles browsed by the user, wherein n is a positive integer greater than 1; extracting article categories of the n historical articles browsed by the user; and determining the interest vector weight of each article category based on the article categories of the n historical articles and a tap frequency, a time attenuation factor, and a weight of each article category.”
Dolan teaches “wherein before sending the user behavior information of the user (e.g., a user’s interests), the method further comprises: obtaining n historical articles browsed by the user, wherein n is a positive integer greater than 1; extracting article categories of the n historical articles browsed by the user; and determining the interest vector weight of each article category based on the article categories of the n historical articles and a tap frequency, a time attenuation factor, and a weight of each article category” (Figs. 1, 2B, 2C, 2D, 2E, ¶ [0006], a system and method are provided to provide personalized news recommendations based on a prediction of a user's interests. The prediction of the user's interest is based on the user's selection history … This enables a user to receive news recommendations for news items in the categories the user has a strong interest; ¶ [0067-0068], A particular user's interest for each category (or probability of selecting media items belonging to each category c) during a time period t is determined using the particular user's click distribution (e.g., 130) … a particular user's interest in a respective category ci (or probability of selecting an item belonging to category c) at any given time t is represented by the equation … In Equation 1, the probability of a particular user clicking on a media item (e.g., 126, 129) of category ci at time t is represented by pt(category=ci|click). For example, a particular user may click on health related media items 13% of the time. In Equation 1, pt(category=ci|click) corresponds to the particular user's click distribution (e.g., 130) during time period t for the respective category In Equation 1, pt(category=ci) is the probability that a media item (e.g., 126, 129) belongs to category ci during time period t. For example, in the last month, there is a 13% chance a given media item belongs to sports. In Equation 1, pt(category=ci) corresponds to the proportion of media items published in category ci during time period t and to the trend of news during time period t … The probability of the particular user clicking on any article at time t is represented by pt(click) … To accurately predict a particular user's genuine interest in a category ci, the particular user's interest (pt(click|category=ci)) in multiple time periods is combined as follows … M represents the total number of time windows combined; ¶ [0059], the click distribution (e.g., 130 of the particular user determines the particular user's likelihood of selecting media items associated with a respective category. For example, if 20% of the particular user's clicks were for technology, the particular user is likely to selection technology items 20% of the time. In some embodiments, a combination of weighted click data is used to determine the particular user's likelihood of selection. For example, 5% of the particular user's clicks may have been for health items but the determined likelihood of the particular user selecting health items may be greater than 5% due to weighted click data. For example, search clicks may be given greater weight than browse clicks. Clicks with shorter selection duration may be given greater weight than clicks with longer selection duration; ¶ [0073], click rates (e.g., the total number of users who clicked on an item divided by the number of times the item was displayed to users); ¶ [0032], media items 129 including but not limited to news articles; ¶ [0041], the clicks 260 include the total number of clicks for the respective category 214 during a predefined period of time. For example, for the category of Sports, a user may have had a total of 25 clicks in the past week).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine determining a user’s interest of an article category based on historical articles, a tap frequency, a time attenuation factor, and a weight as taught by Dolan into determining a user’s interest of an article category as taught by Bitran-Moon. One of ordinary skill in the art would have been motivated to do so because Dolan recognizes that it would have been advantageous to consider a user’s selection history to determine the user’s interest in categories of news/articles and provide news recommendations accordingly (¶ [0006], a system and method are provided to provide personalized news recommendations based on a prediction of a user's interests. The prediction of the user's interest is based on the user's selection history and the selection history of a community of users or general population. This enables a user to receive news recommendations for news items in the categories the user has a strong interest in) (KSR(G), TSM, MPEP 2143). Additionally, this is combining prior art elements according to known methods to yield predictable results, specifically, combining known methods of how to determine a user’s interest in articles to yield predictable results, especially given that Bitran, Moon, and Dolan are in the same field of endeavor of providing recommended articles based on a user’s interest (KSR(A), MPEP 2143).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/HANNAH S WANG/Supervisory Patent Examiner, Art Unit 2631
