DETAILED ACTION
This action is responsive to amendments filed on July 28, 2026.
Amendments filed on July 28, 2026, have been acknowledged and considered.
Claims 1, 5, 10, 15 and 26-30 have been amended. Claims 4, 9, 11, 21 and 25 were previously canceled.
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 .
Response to Amendment
Applicant's Remarks, filed July 28, 2026, have been fully considered and entered.
Accordingly, Claims 1-3, 5-8, 10, 12-20, 22-24 and 26-30 are pending in this application. Claims 1, 5, 10, 15 and 26-30 have been amended. Claims 4, 9, 11, 21 and 25 have previously been canceled. Claims 1 and 15 are independent claims. In light of Applicant’s amendments, the 35 U.S.C 112(b) rejection of claims 5 and 28 have been withdrawn.
Response to Arguments
Applicant’s arguments, see pages 9-10, filed July 28, 2026, with respect to the amendments of independent claims 1 and 15 have been fully considered, but they are moot in view of new grounds of rejection necessitated by amendment.
Argument 1: Applicant argues on page 9 of Applicant Arguments and Remarks “Applicant submits that neither of the cited references teaches or suggests the amended limitation reciting, in part:
" determining, based on the browser history, that the cluster is associated with at least
one search continued across a plurality of sessions;
" selecting the cluster for generation of a user interface based on determining that the
cluster is associated with the at least one search continued across the plurality of
sessions;
" determining, based at least on the cluster being associated with the at least one search
continued across the plurality of sessions, a relevance score for the cluster;
" in response to determining that the relevance score meets a threshold, generating the
user interface for the cluster, the user interface being configured to enable resumption
of the at least one search...”
Response to Argument 1: Examiner respectfully disagrees. Applicant does not identify what the references disclose, does not explain how any disclosure falls short, and does not identify any structural or functional distinction between the claimed subject matter and the applied art. A general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references does not comply with 37 C.F.R. § 1.111(b) and is unpersuasive. Applicant’s arguments should be more than mere conclusory statements for to establish a position which the Applicant must provide clear rationale supporting the determination and articulate their disagreement regarding any part of the cited art. Applicant must provide appropriate analysis of the corresponding claimed limitation, and such analysis must be supported by the originally filed specification.
The amended limitations are now addressed by Birch (US 20200042567 A1) which was already of record (applied to claims 5 And 26 in the prior Office Action), in view of new grounds of rejection necessitated by amendment.
Regarding "determining, based on the browser history, that the cluster is associated with at least one search continued across a plurality of sessions;” Birch [0059, 0063, 0076, 0083, 0090] teaches that the group of web pages in a search activity that continues across sessions: the group represents a task, which Birch defines as a web searching activity related to the same or similar subject matter [0059], each constituent navigation tree starts with a search entered into the browser’s search box [0083], and a group is formed only when two navigation trees are determined to be topically-related to each other [0090], so when the user returned and search the same subject a second time, the resulting group is a “journey” defined over a period of time that may span across multiple browsing sessions over multiple days (or weeks) and includes pages from closed tabs [0076], and the underlying data includes search terms entered and information from prior browser instances/sessions [0063], so the determination is made from browsing history data spanning prior sessions. See rejection of claim 1 below.
Regarding "selecting the cluster for generation of a user interface based on determining that the
cluster is associated with the at least one search continued across the plurality of
sessions;” Birch [0090, 0113, 0115] teaches that only groups satisfying the multi-session, multi-search condition become candidates for the interface, where a group is only generated upon two topically related navigation trees determination, and upon that determination the system provides one or more navigation suggestions on the user interface [0090], where operation 906 the selects a group of web pages from the one or more groups, the selected group representing a task that is carried out by a user [0113] and operation 908 provides a navigation suggestion for display on a user interface of the web browser based on the selected group [0115]. See rejection of claim 1 below.
Regarding "determining, based at least on the cluster being associated with the at least one search continued across the plurality of sessions, a relevance score for the cluster;” Sadahiro [0046, 0048, 0052-0053] teaches computing a per-cluster relevance score from per page factors that directly measure repeated return to the cluster’s pages over a multi-day (Thus, multi-session) window, where a total visit factor equal to a number of visits made to a particular web page in the last time period (e.g. 14 days) [0052], a recency factor selected across the same 14 day window [0048], each multiplied by a coefficient and the summed or otherwise combined to determine a score for each cluster [0053] which the cluster relevancy evaluator calculates for each of the clusters [0046]. Birch [0092] provides a group level measure based on the number of times a particular web page was viewed, interacted with or loaded. Thus, Sadahiro-Birch teaches this limitation, where the cluster being scores is Birch’s multi-session continued search journey, and Sadahiro’s total-visit factor counts the repeat returns that represent continuing that search across sessions. Thus, a journey the user returned to on multiple days accumulates a higher score than one visited once. See claim 1 rejection below.
Regarding "in response to determining that the relevance score meets a threshold, generating the user interface for the cluster, the user interface being configured to enable resumption
of the at least one search...” Sadahiro [0056, 0061, 0069] teaches that the cluster selector receives the clusters and their corresponding scores, selects clusters to provide to a user above a certain threshold, identifies clusters above a predetermined threshold and outputs only those clusters as selected cluster presented to the user in a graphical user interface. Sadahiri [0005] provides the cluster’s page as a suggested web page to revisit, and Birch [003, 0054, 0070] teaches that the navigating suggestion includes one or more selectable elements that assist the user to complete a task, comprises a list of previously rendered web pages that the user is likely to return to complete the task, presented as selectable user interface elements, where the user may not need to open a new browser tab to re-search, reducing the time required to re-search or re-find relevant web pages to accomplish the task. See rejection of claim 1 below.
Sadahiro and Birch are in the same field of endeavor and address the same problem; the difficulty of re-finding pages from an interrupted research task (Sadahiro [0027], Birch [0051]). Birch [0070] explicitly states that its multi-session journey reduces the browser tabs launched and the execution time to re-search, thereby decreasing the number of computational resources consumed by the computing device, and increasing the efficiency of the web browser itself.
Therefore, the examiner has determined that this argument is not persuasive.
Claim Objections
Claims 15 and 26 are objected to because of the following informalities:
In claim 15 “being configured enable resumption” should read “being configured to enable resumption”
In claim 26 “an image that meet inclusion criteria” should read “an image that meets inclusion criteria”
In claim 26 “wherein identifying the cluster further includes determining” should read “wherein the instructions to identify the cluster further include determining” for consistency with its parent claim 15, which recites a system whose memory is “configured to: identify… a cluster.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5 and 27-28 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites “determining that the webpage includes an image meeting that meets inclusion criteria for the user interface; and in response to determining that the webpage includes the image that meets the inclusion criteria, selecting the image for display in the region of the user interface.” Parent claim 1 already requires “generating the user interface for the cluster, the user interface… including a region displaying a webpage title and an image from a webpage of the plurality of webpages”. It is unclear whether the image recited in claim 5 is the same image that claim 1 already displays in the region, in which case it cannot be determined what the selecting step further limits, or claim 5 introduces a second image distinct from the image of claim 1, in which case it cannot be determined whether the region displays one image or two, nor what relationship the second image have to the image already required by claim 1. Examiner request clarification from Applicant. The Specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The metes and bounds of “the image” recited in claim 5 is unclear and thus the scope of the claim is indefinite.
Dependent claims 27 and 28 are also rejected as depending from claim 5 and further reciting “the image” and “the inclusion criteria”. And are therefore indefinite for the same reasons with respect to claim 5.
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 1-3, 5-7, 10, 12, 15-18, 26 and 29-30 are rejected under 35 U.S.C. 103 as being unpatentable over Sadahiro (US Patent Application Publication No. US 20200380051 A1 - hereinafter Reference1), in view of Birch (US Patent Application Publication No. US 20200042567 A1).
Regarding claim 1, Reference1 teaches a method, the method comprising: identifying a cluster that includes a plurality of webpages from a browser history associated with a user; (See Reference1 [0005, 0056] “correlation scores are calculated that indicate correlations between web pages indicated in a browsing history of a user [Thus, associated with a user]… The web pages are clustered into a plurality of clusters based on the correlation scores… Cluster selector 310 is configured to identify a cluster from the plurality of clusters and provide an indication of a cluster of web pages… to provide to a user as one or more suggested web pages to revisit” [Thus, identifying a cluster that includes a plurality of webpages from a browser history associated with a user])
Reference1 does not explicitly disclose determining, based on the browser history, that the cluster is associated with at least one search continued across a plurality of sessions;
However, Birch teaches determining, based on the browser history, that the cluster is associated with at least one search continued across a plurality of sessions; (See Birch [0059, 0063] “the server 102 may determine that the user is performing a task based on the data 101 [e.g. determining based on the browser history]. A task may be a web searching activity related to the same or similar subject matter. In some implementations, the task may refer to an activity of a single topic or category that is carried out by navigating the web browser 122… the data 101 includes search terms entered, contextual information (e.g., history of navigation of users or for other users, time spent, trends), user profile information, information from prior browser instances/sessions, and/or information from a different browser. [Thus, browsing history spanning prior sessions]” See also Birch [0083] “the navigation tree builder 104 may generate a new navigation tree 114 when a user starts a search (e.g., entering one or more terms into a search box of the web browser 122)… each navigation tree 114 may start with a search or a bookmark, and as the user navigates from a page or search results… the navigation tree builder 104 may create page nodes that correspond to the different web pages 121” See also Birch [0090] “the generation of a particular group of web pages 121 occurs when at least two navigation trees 114 are determined to be topically-related to each other [e.g. the same search continued second time]” See also Birch [0076] “the first group 116 of web pages 121 may be considered a journey (i.e., a real-world task carried out by the web browser 122) which occurs over time… a particular group of web pages 121 [e.g. the cluster] may be defined over a period of time, and may span across multiple browsing sessions over multiple days (or weeks) [e.g. continued across a plurality of sessions]… the web pages 121 of the first group 116… are web pages 121 from previously opened or closed browser tabs 126… a mixture of web pages 121 from currently-open browser tabs 126 and web pages from closed browser tabs 126.” [Thus, determining, based on the browser history, that the cluster is associated with at least one search continued across a plurality of sessions])
Both Reference1 and Birch group a user’s previously visited webpages from browsing history into topical clusters and obtain pages from a cluster so the user can go back to them. Reference1 identifies and ranks such clusters and presents pages of the identified cluster as suggested web pages to revisit. Birch defines the group it provides in the navigation suggestion as a “journey” formed from at least two topically related search rooted navigation trees and defined over a period of time, which may span across multiple browsing sessions over multiple days (Birch [0076]).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Reference1, which identifies a cluster of web pages from a user’s browsing history and provides pages of that cluster to the user as suggested web pages to revisit, to incorporate the teachings of Birch of determining, from the browsing history data spanning prior browsing sessions, that a cluster corresponds to a search the user has continued across a plurality of browsing sessions.
One would have been motivated to do so to limit Refgerence1’s suggestions to the clusters representing a task the user is still carrying out and is likely to return to in order to complete it, reducing the number of browsers tabs that otherwise would be launched to accomplish that task and the execution time required to re-search or re-find relevant web pages to accomplish the task, thereby reducing computational resources utilization and increasing the efficiency of the web browser (Birch [0070]).
Reference1 further in view of Birch, [hereinafter Reference1-Birch] additionally disclose selecting the cluster for generation of a user interface based on determining that the cluster is associated with the at least one search continued across the plurality of sessions; (See Birch [0090] “the generation of a particular group of web pages 121 [e.g. the cluster] occurs when at least two navigation trees 114 are determined to be topically-related to each other [e.g. determining that the cluster is associated with the at least one search continued across the plurality of sessions]… the system 100 may determine that the user is carrying out the task, and provide one or navigation suggestions 128 on the user interface 124 of the web browser 122 [e.g. selecting the cluster for generation of a user interface]” See also Birch [0113-0115] “Operation 906 includes selecting a group of web pages 121 from the one or more groups of web pages 121 that are determined to be topically-related to content displayed in the web browser 122… The selected group may represent a task that is carried out a user of the web browser 122. [e.g. multi-session journey of Birch [0076]]… providing a navigation suggestion 128 for display on a user interface 124 of the web browser 122 based on the selected group, where the navigation suggestion 128 includes one or more user-selectable elements that assist the user to complete the task.”)
determining, based at least on the cluster being associated with the at least one search continued across the plurality of sessions, a relevance score for the cluster; (See Reference1 [0046-0048, 0052-0053] “Cluster relevancy evaluator 308 is configured to rank the clusters for relevancy to the user… based on a relevancy algorithm… Cluster relevancy evaluator 308 is also configured to calculate a relevancy score [e.g. a relevance score of the cluster] for each of the clusters based on the determined likelihoods… The relevancy algorithm may be configured to take into account any combination of the following factors… Recency—the recency factor corresponds to how recent (e.g., how many minutes ago, hours ago, days ago, etc.) the user visited a particular web page… if the user visited the web page today, the recency factor value may be a “1.00”… while if the web page was visited 14 days ago or greater, the recency factor value may be a “0.00”… Total visits—the total visits factor corresponds to a number of visits made to a particular web page in the last time period (e.g., 14 days) [e.g. a measure of how many times the user came back to the cluster’s pages across multiple days across the plurality of sessions]… each included factor may be multiplied by a coefficient so a score in a desired range may be generated (e.g., 0.00 to 1.00) for each page of the clusters… The scores for the pages in a cluster may be summed or otherwise combined to determine a score for each cluster [e.g. the relevance score for the cluster]” See also Birch [0092] “The user engagement metrics may include the number of times a particular web page 121 was viewed, interacted with, or loaded, the amount of time spent on a particular web page 121”
Thus, in the combination, the cluster being scored is Birch’s multi-session continued search journey. Refernce1’s computes that cluster’s score by summing the per-page factors, one of which is total visits in the last time period (e.g., 14 days), which represents a count of search across sessions: a journey the user returned to on multiple days accumulates a higher total visits value and therefore a higher cluster score that one visited once. The relevance score is thus determined based at least of the cluster being associated with a search continued across a plurality of sessions.)
in response to determining that the relevance score meets a threshold, generating the user interface for the cluster, (See Refrence1 [0056, 0061] “cluster selector 310 may receive a cluster ranking 324 from cluster relevancy evaluator 308 and select clusters to provide to a user above a certain threshold… cluster selector 310 may receive cluster ranking 324 as a ranking of clusters from cluster relevancy evaluator 308 and identify a cluster from the ranked clusters that have the highest relevancy to the user. In addition, cluster selector 310 may receive… their corresponding relevancy scores, and may identify clusters above a predetermined threshold. [e.g. determining that the relevance score meets a threshold]” See also Reference1 [0069] “Selected cluster information 326 may be presented to the user in a user interface, such by being displayed in a graphical user interface (GUI) [e.g. generating the user interface for the cluster]”)
the user interface being configured to enable resumption of the at least one search and (See Reference1 [0005] “A cluster having a greatest ranking is identified and an indication of a web page of the identified cluster as a suggested web page to revisit is provided to a user” See also Birch [0003] “providing a navigation suggestion for display on a user interface of the web browser based on the selected group, where the navigation suggestion includes one or more user-selectable elements that assist the user to complete the task [e.g. configured to enable resumption of the search]” See also Birch [0054] “the navigation suggestion may include a list of previously-rendered web pages that the user is likely to return to complete the task… presented as selectable user interface (UI) elements, where a selection of a UI element causes the web browser to display a respective web page in a browser tab. As such, the user may not need to open a new browser tab to re-search… Rather, when it is determined that the user is currently carrying out a task, the web browser automatically provides a navigation suggestion to the user to help accomplish the task.”)
including a region displaying a webpage title and an image from a webpage of the plurality of webpages, the region being selectable to navigate to an address for the webpage; and causing display of the user interface in a browser. (See Reference1 [0070-0072] “selected cluster information 326 may include a title and a thumbnail of a web page from the one or more web pages that if a user clicks may enable to user to traverse to the web page [Thus, selectable to navigate to an address for the webpage]… As shown in FIG. 8, web browser 800 presents a page that indicates a plurality of clusters 802A-802E [Thus, causing display of the user interface in a browser]. FIG. 8 shows only clusters 802A-802E but any number of indications of a cluster may be displayed to a user… In FIG. 8, clusters 802A-802E are identified topically. For example, cluster 802A is titled “Bahamas” and cluster 802B is titled “Cooking”. Cluster 802A provides several titles of web pages and thumb nails 806 and 808 of web pages related to the Bahamas [Thus, including a region displaying a webpage title and an image from a webpage of the plurality of webpages]. The user may have previously visited these web pages while researching a trip to the Bahamas.”)
Regarding claim 2, Reference1-Birch teaches all limitations and motivations of claim 1, wherein the cluster is further identified by determining that at least one webpage of the plurality of webpages is associated with a page access time that is within a time threshold. (See Reference1 [0048] “Recency—the recency factor corresponds to how recent (e.g., how many minutes ago, hours ago, days ago, etc.) the user visited a particular web page. The more recently the user visited the web page, the greater the value of the recency factor. The longer ago the user visited the web page, the lower the value of the recency factor. For instance, if the user visited the web page today, the recency factor value may be a “1.00” (highest value on a 1.00 to 0.00 scale), while if the web page was visited 14 days ago or greater, the recency factor value may be a “0.00” (lowest value)” See also Reference1 [0053, 0055] also teaches that web pages may be culled out that have a 0 score, meaning that pages outside of the 14-day window (e.g. beyond a time threshold) are excluded from the cluster, and further teaches filtering clusters based on context of usage including time of day, the day of the week or month.
Thus, the cluster is further identified by determining that at least one of its webpage has a page access time within a time threshold.)
Regarding claim 3, Reference1-Birch teaches all limitations and motivations of claim 1, wherein the region is a first region and in response to identifying the cluster the method further includes obtaining a related search suggestion for a cluster topic for the cluster; and the user interface for the cluster further includes a second region displaying the related search suggestion, the second region being selectable to initiate a search using the related search suggestion. (See Reference1 [0071-0073], Fig. 9 “a user may traverse the provided clusters by clicking on an arrow button next to cluster 802E and search clusters using a search bar 804… a user may traverse the provided clusters [Thus, in response to identifying the cluster] by clicking on an arrow button next to cluster 802E and search clusters using a search bar 804… FIG. 9 provides an example of displaying indications of clusters in a browser based on a user's internet search. As depicted in FIG. 9, a user inputted “recipes for” into a search bar [Thus, a second selectable region selectable to initiate a search using the related search suggestion] of a web browser 900. In addition to providing recommendations to complete the statement of “recipes for” [Thus, obtaining/displaying a related search suggestion for a cluster topic for the cluster], web browser 900 recommends clusters 902A-902D related to the user's search to the user.”)
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Regarding claim 5, Reference1-Birch teaches all limitations and motivations of claim 1, further comprising: determining that the webpage includes an image that meets inclusion criteria for the user interface; and in response to determining that the webpage includes the image that meets the inclusion criteria, selecting the image for display in the region of the user interface. (See Birch [0096] “the navigation suggestion 128 may be a user interface (or element) that provides [Thus, display] at least a portion a list of the first group 116 [Thus, in response to identifying the cluster] on the user interface 124 of the web browser 122… the navigation suggestion 128 identifies the title (or short phrase describing the page) of each of the web pages 121 of the first group 116 [e.g. first webpage included in the at least one webpage] … the navigation suggestion 128 displays a representative image [Thus, an image meeting inclusion criteria for the user interface] associated with one or more of the web pages 121. [Thus, determining that the webpage includes an image meeting inclusion criteria for the user interface]”)
Regarding claim 6, Reference1-Birch teaches all limitations and motivations of claim 1, wherein the region is a first region, the webpage is a first webpage, and the webpage title is a first webpage title and the user interface for the cluster further including a second region displaying a second webpage title from a second webpage of the plurality of webpages, the second region being selectable to navigate to an address for the second webpage. (See Reference1 Fig. 8 and [0070-0072] “FIGS. 8 and 9 provide example embodiments of how web pages [e.g. first and second webpages] of an identified cluster may be presented to a user in a web browser [e.g. user interface for the cluster]… In FIG. 8, clusters 802A-802E are identified topically. For example, cluster 802A is titled “Bahamas” and cluster 802B is titled “Cooking” [(e.g. first and second webpage titles) Thus, including a second region displaying a second webpage title from a second webpage of the plurality of webpages]. Cluster 802A provides several titles of web pages and thumb nails 806 and 808 of web pages related to the Bahamas. The user may have previously visited these web pages while researching a trip to the Bahamas. The user may click the titles or thumb nails 806 and 808 provided in cluster 802A to access these web pages that she previously has visited. [Thus, the second region being selectable to navigate to an address for the second webpage]”)
Regarding claim 7, Reference1-Birch teaches all limitations and motivations of claim 6, wherein the first webpage is associated with a higher ranking than a ranking of the second webpage, and wherein the first webpage is assigned to the first region based on the higher ranking. (See Reference1 [0046, 0053-0056] “Cluster relevancy evaluator 308 may use the likelihood values associated with web pages in a cluster to filter out web pages in the cluster (e.g., web pages below a threshold) and rank the web pages within the cluster… All scores may be maintained to provide to the user any combination of the clusters (e.g., the highest three ranked clusters), and/or the any combination of the web pages (e.g., the highest two ranked pages) [e.g. first webpage is associated with a higher ranking than a ranking of the second webpage]… cluster selector 310 may select only the highest ranked clusters (e.g., the top three) and provide indications to the user of one or more web pages [e.g. first webpage is assigned to the first region based on the higher ranking] from each of the highest ranked clusters”)
Regarding claim 10, Reference1-Birch teaches all limitations and motivations of claim 1, wherein the relevance score for the cluster is further based on a number of times the cluster is displayed during a recent timeframe. (See Reference1 [0024, 0038] “a user inputs a link to a web page (e.g., a Uniform Resource Locator (URL)) into a web browser of a user computing device. The web browser of the user computing device retrieves the web page from a remote web server (e.g., using Hypertext Transfer Protocol (HTTP)) and displays the web page on the user computing device [e.g. each visit to a web page is an instance of that web page being displayed in the browser]… The user may input a link to a web page into web browser 208. Browser 208 may retrieve the web page over network 212 based on the link and display the retrieved web page on display window 206.” See also Reference1 [0052-0053] “Total visits—the total visits factor corresponds to a number of visits made to a particular web page in the last time period (e.g., 14 days) [i.e. a count during a recent timeframe of the times that web page (e.g. a member of the cluster) was displayed in the browser]. To determine this factor for a particular page, the number of visits to that page may be divided by a total number of page visits by the user during that time period… each included factor may be multiplied by a coefficient so a score in a desired range may be generated (e.g., 0.00 to 1.00) for each page of the clusters... The scores for the pages in a cluster may be summed or otherwise combined to determine a score for each cluster [e.g. the display counts of the cluster’s web pages are aggregated into a relevance score for the cluster (Thus, the relevance score for the cluster is therefore further based on a number of times the cluster is displayed during a recent timeframe)]”)
Regarding claim 12, Refrence1-Reference2 teaches all limitations and motivations of claim 1, wherein the higher ranking of the first webpage is based at least on determining that the first webpage is associated with a list of saved items. (See Reference1 [0047-00] “The relevancy algorithm may be configured to take into account any combination of the following factors… the bookmarked factor corresponds to whether the user bookmarked a particular web page. If the user bookmarked [Thus, associated with a list of saved items] the web page, the greater the bookmarked factor value (e.g., “1.00”) [e.g. higher ranking of the first webpage is based at least on determining that the first webpage is associated with a list of saved items], while if the user did not bookmark the web page, the lower the bookmarked factor value (e.g., “0.00”).” Examiner notes that bookmarks are a list of saved items.
Regarding claim 15, Birch-Mancuso-Mehta teaches all of the elements of claims 1 and 6 in method form rather than system form. Therefore, the supporting rationale of the rejection of claims 1 and 6 applies equally as well to those elements of claim 15.
Regarding claim 16, Birch-Mancuso-Mehta teaches all of the elements of claim 2 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 2 applies equally as well to those elements of claim 16.
Regarding claim 17, Birch-Mancuso-Mehta teaches all of the elements of claim 3 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 3 applies equally as well to those elements of claim 17.
Regarding claim 18, Birch-Mancuso-Mehta teaches all of the elements of claim 7 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 7 applies equally as well to those elements of claim 18.
Regarding claim 26, Refrence1-Birch teaches all of the elements of claim 5 in method form rather than system form. Therefore, the supporting rationale of the rejection to claim 5 applies equally as well to those elements of claim 26.
Regarding claim 29, Reference1-Birch teaches all of the elements of claim 10 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 10 applies equally as well to those elements of claim 29.
Regarding claim 30, Reference1-Birch teaches all limitations and motivations of claim 1, wherein the relevance score for the cluster is further based on a number of times a category is displayed during a recent timeframe. (See Reference1 [0054] “each cluster may be identified in any manner… A title for a cluster may be determined… by performing a semantic analysis of the web pages included in the cluster to determine a context of the pages, and using the determined context as the cluster title (e.g., London vacation, Seattle Mariners, etc.) [e.g. the cluster’s web pages share the cluster’s category]” See also Reference1 [0072] “In FIG. 8, clusters 802A-802E are identified topically. For example, cluster 802A is titled “Bahamas” and cluster 802B is titled “Cooking” [e.g. each cluster corresponds to a category]” See also Reference1 [0047, 0051-0053] “The relevancy algorithm may be configured to take into account any combination of the following factors… Category—the category factor corresponds to whether a particular web page is in a same category (e.g., sports, particular sports such as football, news, entertainment, social media, etc.) as the web page the user was just looking at [e.g. web pages are tracked by category]… Total visits—the total visits factor corresponds to a number of visits made to a particular web page in the last time period (e.g., 14 days) [e.g. a count of displays of pages of that category within a recent timeframe]… The scores for the pages in a cluster may be summed or otherwise combined to determine a score for each cluster.” [Thus, the relevance score for the cluster is further based on a number of times a category is displayed during a recent timeframe])
Claims 20 is rejected under 35 U.S.C. 103 as being unpatentable over Reference1-Birch, in view of Eichstaedt (US Patent Publication No. US 6385619 B1- hereinafter Reference2).
Regarding claim 20, Reference1-Birch2 teaches all limitations and motivations of claim 15, wherein the memory is further configured with instructions to modify the relevance score based on a category boost list, the category boost list including categories representing tasks that span multiple browsing sessions. (See Reference1 [0046-0055] “cluster relevancy evaluator 308 may rank the clusters for relevancy to a user based on a relevancy algorithm. For example, the relevancy algorithm may determine a likelihood that a user will access particular web pages of a cluster. Cluster relevancy evaluator 308 may use a machine learning model trained on other users' browsing history [i.e. tasks that span multiple browsing sessions] to assign the likelihoods to web pages… The relevancy algorithm may be configured to take into account any combination of the following factors… Category—the category factor corresponds to whether a particular web page is in a same category (e.g., sports, particular sports such as football, news, entertainment, social media, etc.) [e.g. category boost list including categories representing tasks that span multiple browsing sessions] as the web page the user was just looking at. If so, the category factor value may be a “1.00” (highest value) [Thus, modify the relevance score based on a category boost list]. If not, the currency factor value may be a “0.00” (lowest value) … Web pages may be culled out that have a 0 score. The scores for the pages in a cluster may be summed or otherwise combined to determine a score for each cluster… cluster relevancy evaluator 308 may exclude clusters having low relevancy at certain times of a day.” See also Birch [0076] “the first group 116 of web pages 121 may be considered a journey (i.e., a real-world task carried out by the web browser 122)… may be defined over a period of time, and may span across multiple browsing sessions over multiple days (or weeks)” See also Birch [0059] “Some non-limiting examples may include researching a hiking trip in a certain area, researching dog breeds, researching a particular movie to see in a movie theater, or for purchasing a vacuum cleaner on the Internet [e.g. an enumerated set of multi-session task categories]”)
Reference1-Birch does not explicitly disclose that the categories which modify the relevance score are maintained as a list.
However, Reference2 also teaches that the categories which modify the relevance score are maintained as a list. (See Reference2 abstract “the profiles also are generated based on other factors including the frequency [e.g. tasks that span multiple browsing sessions] and currency of visits to documents having a given classification [i.e. category], and/or the hierarchical depth of the levels or parts of the documents viewed. User profiles include an interest category code and an interest score to indicate a level of interest in a particular category. The profiles are updated automatically to accurately reflect the current interests of an individual, as well as past interests. A time-dependent decay factor is applied to the past interests.” See also Reference2 Col. 3, lines 26-67, Col. 4, lines 1-8 “Ranking Categories… The present system represents the user interest as a disjunction of interest categories. The basic interest units are the categories that are defined by the taxonomy tree [i.e. category boost list]… When a user has not clicked on documents from a certain category for a predetermined length of time (e.g., a week, or a month), the weight of the corresponding category will drop… A scoring function s(w, r) then assigns a new weight to a category based on the previous weight w of that category and the result r=i(vs,cc,tc) of the interest function. We use a decay in the scoring function to express the fact that older votes become less important over time [e.g. modify the relevance score based on a category boost list].”)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Reference1-Birch, whose relevance algorithm raises a cluster’s relevance score when the cluster’s web pages are in the same category as the page the user was just looking at, to incorporate Reference2 maintained taxonomy of interest categories in which each category carries a weight derived from the frequency and currency of the user’s visit to documents of that category.
Reference1’s relevancy algorithm is a known system being configured to take into account any combination of scoring factors (Reference1 [0047]), and Reference2’s per-category interest weighting is a known technique for measuring which categories matter to a user from that user’s own access history. Applying the known technique to the known system requires no more that using each element for its established function and would have yielded the predictable result of a cluster relevance score being modified according to categories held in a list, each carrying its own value.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Reference1-Birch, in view of Kumar (US Patent Application Publication No. US 20180367848 A1).
Regarding claim 8, Reference1-Birch teaches all limitations and motivations of claim 7, wherein the image is a first image and the second region includes a second image, and the higher ranking of the first webpage is based at least on a size and a resolution of the first image. (See Reference1 Fig. 8, [0056, 0072] teaches ranking web pages and display of images (thumbnails) in multiple regions (thumb nails 806 and 808).
Reference1-Birch does not explicitly disclose ranking the webpages based on a size and resolution of the first image.
However, Kumar teaches the higher ranking of the first webpage is based at least on a size and a resolution of the first image in more details. (See Kumar [0039-0045] “detecting (202) a plurality of webpages based on one of an interest corresponding to the at least one user and the user-input; retrieving (203) content from the detected plurality of webpages… the step of detecting (202) further comprises the steps of: identifying (207) a first set of web pages based on one of the interest corresponding to the at least user and the user-input; and selecting (208) the plurality of webpages from the first set of webpages based on at least one of a metadata [e.g. ranking of the first webpage] associated with the first set of webpages and content [e.g. image] of the first set of webpage matching the user-input… the metadata associated with a webpage includes: page rank of the web page… the interest corresponding to the at least one user includes one or more of: browsing history… most-visited webpages, recently visited webpages” See also Kumar [0089] "the content selecting unit (407) selects the content from the detected webpages, including the extended webpages, based on size of the display unit, font size of the content, resolution of the content (for example, image resolution, and viewing parameters with respect to the display unit. [Thus, based at least on a size and a resolution of the first image]”
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Refrence1-Reference2 which ranks web pages and display of images (thumbnails) in multiple regions of a user interface, to incorporate the teachings of Kumar of selecting the content from the detected webpages based on size and resolution (e.g. image resolution, and viewing parameters with respect to the display unit.)
One would be motivated to do so to enhance user experience by optimizing the rendering of content based on viewing parameters, and better inform the user of what the cluster’s pages are about.
Regarding claim 19, Reference1-Birch further in view of Kumar teaches all of the elements of claim 8 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 8 applies equally as well to those elements of claim 19.
Claims 13-14 and 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Reference1-Birch in view of Karam (US Patent Publication No. US 8433995 B1).
Regarding claim 13, Reference1-Birch teaches all limitations and motivations of claim 12, wherein the list of saved items is a collection of bookmarks, the user interface including an indication that the first webpage is bookmarked in the browser. (See Reference1 [0047-0049] “The relevancy algorithm may be configured to take into account any combination of the following factors… the bookmarked factor corresponds to whether the user bookmarked a particular web page. If the user bookmarked [Thus, associated with a list of saved items] the web page, the greater the bookmarked factor value (e.g., “1.00”) [e.g. higher ranking of the first webpage is based at least on determining that the first webpage is associated with a list of saved items], while if the user did not bookmark the web page, the lower the bookmarked factor value (e.g., “0.00”).” Examiner notes that bookmarks are a list of saved items.
Reference1-Birch does not explicitly disclose the user interface including an indication that the first webpage is bookmarked in the browser.
However, Karam teaches the user interface including an indication that the first webpage is bookmarked in the browser in more details. (See Karam Col. 3, lines 56-67, Col. 4, lines 1-15 “The web browser (100) shown in FIG. 1 also contains a toolbar (102), which provides increased functionality to the web browser (100)… “bookmarks” button (106) shows a list of all previously stored bookmarks [Thus, a list of saved items (e.g. fourth region)], for a particular user.” See also Karam Col. 2, lines 27-35 “The graphical user interface can be a toolbar in a browser… Displaying a button can include displaying the button in one of… a third state that indicates that the displayed web page [e.g. first webpage] has been bookmarked [Thus, an indication that the first webpage is bookmarked in the browser]”)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Reference1-Birch to incorporate the teachings of Karam of displaying a visual bookmarked indicator in Reference1’s cluster UI to communicate to the user why a given webpage ranked highly, a predictable use of a known UI technique.
Regarding claim 14, Refrence1-Reference2 teaches all limitations and motivations of claim 12, wherein the list of saved items is a collection of annotations, the user interface including an indication that the first webpage has an associated annotation. (See Karam Col. 4, lines 15-19 & Fig. 5 “this list of bookmarks can be organized in various categories or labels [i.e. collection of annotations], such that a bookmark [e.g. first webpage] for an online sports magazine, for example, can be associated with a “Sports” label and a “News” label [Thus, has an associated annotation], and thus be more easily found by the user. [Thus, the list of saved items is a collection of annotations, the indication indicating the first webpage has an associated annotation]”)
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Thus, the user interface including an indication that the first webpage has an associated annotation.)
Regarding claim 22, Reference1-Birch in view of Karam teaches all the elements of claim 13 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 13 applies equally as well to those elements of claim 22.
Regarding claim 23, Reference1-Birch in view of Karam teaches all the elements of claim 13 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 13 applies equally as well to those elements of claim 23.
Regarding claim 24, Reference1-Birch in view of Karam teaches all the elements of claim 14 in method form rather than system form. Therefore, the supporting rationale of the rejection of claim 14 applies equally as well to those elements of claim 24.
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Reference1-Birch-Birch in view of Kumar (US Patent Application Publication No. US 20180367848 A1).
Regarding claim 27, Reference1-Birch-Birch teaches all limitations and motivations of claim 5.
Reference1-Birch does not explicitly disclose the inclusion criteria relate to angle or size of an object within the image.
However, Kumar teaches the inclusion criteria relate to size of an object within the image in more detail. (See Kumar [0089] "the content selecting unit (407) selects the content from the detected webpages, including the extended webpages, based on [e.g. inclusion criteria] size of the display unit, font size of the content [e.g. size of an object within the image], resolution of the content (for example, image resolution), and viewing parameters with respect to the display unit… This enables selection and subsequent presentation of the multimedia content”
Reference1-Birch-Birch teaches displaying representative image associated with the webpages in the cluster. It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Refrence1-Reference2-Birch to incorporate the teachings of Kumar of selecting the content from the detected webpages based on size including font size of the content [e.g. size of an object within the image].
One would be motivated to do so to enhance user experience by optimizing the rendering of content based on viewing parameters, and better inform the user of what the cluster’s pages are about.
Claim 28 is rejected under 35 U.S.C. 103 as being unpatentable over Reference1-Birch in view of Mancuso (US Patent Application Publication No. US 20240202250 A1).
Regarding claim 28, Reference1-Birch teaches all limitations and motivations of claim 5.
Reference1-Birch teaches determining that a webpage includes an image meeting inclusion criteria for the user interface and selecting that image for display in the region (Birch [0096, 0101]).
Reference1-Birch does not explicitly disclose wherein the inclusion criteria are defined by a machine model trained on features of training images.
However, Mancuso teaches wherein the inclusion criteria are defined by a machine model trained on features of training images, and (See Mancuso [0099, 0101] "the content scene system 102 utilizes an object detection machine learning model to analyze pixels of the digital image to predict classifications of depicted objects [e.g. a machine model operating on features extracted from images]… the content scene system 102 can utilize a topic prediction machine learning model to generate predictions of topic classifications associated with a content item based on inputting the object classifications, titles, keywords, and/or headers of the content item into the topic prediction machine learning model… the topic prediction machine learning model can generate a topic vector for a content item and can determine distances of the topic vector to topic classification vectors in a vector space [e.g. inclusion criteria defined by the machine model]” See also Mancuso [0118-0123] “As part of training the content cluster machine learning model 608, the content scene system 102 accesses sample data from a database 606… the content scene system 102 identifies sample data such as topic data 602 [e.g. images] and focus data 604 [e.g. training data]… the content scene system 102 inputs the sample data into the content cluster machine learning model 608 and utilizes the content cluster machine learning model 608 to generate a prediction from the sample data… the content scene system 102 compares the content cluster 610 with a stored result 614 (e.g., a ground truth content cluster… using a loss function such as a mean squared error loss function or a cross entropy loss function to determine an error or a measure of loss [e.g. training on sample features]… Based on the comparison 612, the content scene system 102 modifies parameters of the content cluster machine learning model 608… to reduce a measure of error or a loss… repeat the process… until the content cluster machine learning model 608 satisfies a threshold measure of loss [e.g. a trained machine model]” See also Mancuso [0083] “For example, the content scene system 102 analyzes topic data such as… images… the content scene system 102 can determine a topic or a theme for a digital image by combining analysis of its file name in conjunction with recognition of one or more objects or scenes depicted in the digital image as well as a determination that the image is located with other content items relating to a particular topic [e.g. the model’s learned criteria define what qualifies an image as belonging to the topic]”)
wherein the machine model is used to determine whether that the webpage includes the image that meets the inclusion criteria for the user interface. (See Mancuso [0064] “As a subset of content items, a “web content item” refers to a content item accessible via the internet, such a webpage… identified by, or located at, a URL address.” See also Mancuso [0099-0100] “the content scene system 102 utilizes an object detection machine learning model to analyze pixels of the digital image to predict classifications of depicted objects [e.g. applying the trained model to the candidate image]. From a combination of object classifications, titles, keywords, and/or headers, the content scene system 102 can determine a topic or theme for a content item [e.g. the model’s output determines whether the image qualifies]” See also Mancuso [0088, 0130] “the content scene system 102 generates and provides a content restore element that is selectable to restore for presentation one or more content items within a content cluster… the content restore element indicates the content items within the cluster [e.g. the user interface element]… determining return visit likelihood scores for the two or more digital content items within the content cluster based on the focus data and, based on the return visit likelihood scores, generating the content restore element to visually indicate content items from the content cluster that satisfy a threshold return visit likelihood score [e.g. the model derived determination of which content items are placed in the user interface (Thus, machine model is used to determine whether that the webpage includes the image that meets the inclusion criteria for the user interface)]”)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Reference1-Birch, which determines that a webpage includes a representative image meeting criteria for inclusion in the cluster user interface and selects that image for display (Reference1 [0062, 0072], Birch [0096, 0101]), to incorporate the teachings of Mancuso of applying a machine model trained against ground truth indications and applied to pixels of candidate image to determine whether that image qualifies.
One would have been motivated to do so because the region of the cluster user interface holds a single image for each web page which let a user recognize the page on sight, and a model that examined the pixels and classifies the objects depicted gives the system knowledge of what each candidate actually shows, so the image placed in the region depicts the subject matter the user was researching. Thus, it would predictably improve the user’s ability to recognize the intended cluster and improve the cluster suggestion results.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/OSCAR WEHOVZ/Examiner, Art Unit 2161
/APU M MOFIZ/Supervisory Patent Examiner, Art Unit 2161
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