DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/24/2025 has been entered.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1-3, 5-7, 11-12, 14-16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Taylor, Paulet et al (PGPUB Document No. 20230252099), hereafter referred as to “Taylor”, in view of Evans, David (PGPUB Document No.
20220353226), hereafter, referred to as “Evans”, in view of Beukema, Peter (PGPUB Document No. 20230046572), hereafter, referred to as “Beukema”, in further view of Maycock; Rena (PGPUB Document No. 20180349502), hereafter, referred to as “Maycock”.
Regarding Claim 1(Currently Amended), Taylor teaches An active web- based content filtering system, comprising: a user device in communication with a backend server, the user device comprising(Taylor, Fig.3 and para 0028 discloses web-based content filtering system “The scanning may parse the contents of the web page for possible matches to the search term filtered by the contextual information”): a memory for storing a user restrictions file received from the backend server, the user restrictions file comprising one or more user dislikes(Taylor, element 314 of Fig. 3 and para 0040 disclose a content preference storage (like/dislikes) “The web browser session 360 includes access to context information preferences 314 that are stored for the user providing preferences of the context information that they want to apply when accessing web page content”);
an interactive user interface(Taylor, element 311 of Fig. 3 discloses an interactive search page); and a processor, the processor implementing a web browser add-on configured to: intercept an incoming webpage before reaching a web browser of the user device and prior to display on the interactive user interface, the incoming webpage based on a user input(Taylor, Fig. 3 and para 0053 disclose a web-based content filter that intercepts content requests “As soon as the results page is selected, the described post-search plug-in intercepts that page and begins scanning its contents in preparation for constructing a new header that will precis the most relevant parts of the page…”);
request, over a network, the user restrictions file from the backend server; receive the user restrictions file; extract the one or more user restrictions and/or dislikes from the user restrictions file(Taylor, element 314 of Fig. 3 and para 0040 disclose extracting/obtaining from content preferences storage (likes/dislikes or restriction file) “The web browser session 360 includes access to context information preferences 314 that are stored for the user providing preferences of the context information that they want to apply when accessing web page content”);
determine undesired incoming webpage display content by comparing each of the extracted user restrictions and dislikes with the parsed display content from the incoming webpage to determine if each user restriction or dislike directly or indirectly matches the extracted content(Taylor, para 0028 content is being parsed as per user’s preferences (likes/dislikes) for filtering web contents to be displayed “The scanning may parse the contents of the web page for possible matches to the search term filtered by the contextual information”).
But Taylor does not explicitly teach parse display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content; where a direct match relies on similarity of a group comprising words and images, and an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match, wherein the at least one degree of logical separation leads from an extracted user restriction or dislike to parsed content from the incoming webpage that is different from the extracted user restriction or dislike but is related through a logic path with at least one logical step; create a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed, wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and display the filtered webpage to the user.
However, in the same field of endeavor of performing contextual semantic
analysis of words and images Evans teaches parse display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content(Evans, para 0156 teaches contextual understanding of any extracted contents (parsed) by natural language processing “Feature extraction controller 1522 may include a neural network data model configured to predict (e.g., extract) contextual or related text terms based on generation of vectors (e.g., word vectors) with which to determine degrees of similarity ….. feature extraction controller 1522 may be configured to implement a “word2vec” natural language processing algorithm”); where a direct match relies on similarity of a group comprising words and images, and an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match, wherein the at least one degree of logical separation leads from an extracted user restriction or dislike to parsed content from the incoming webpage that is different from the extracted user restriction or dislike but is related through a logic path with at least one logical step(Evans, para 0158 discloses matching data such as words or images to find the degree of similarity, here the degree of similarity suggests direct or indirect matching or degree of logical separation for matching “data representing a portion of an electronic message may be correlated to match at least one subset of disposition metrics to form a correlation data value, …. … algorithms configured to determine a degree of similarity, such as an algorithm configured to implement a cosine similarity algorithm (or equivalent) to identify a measure of similarity between data (e.g., vectors) representing text data (e.g., text-based data 1505 or extracted feature data 1503) and/or image data of supplemental data 1504”; where prior art Taylor teaches restriction data and parsed contents);
Using the broadest reasonable interpretation consistent with the specification (paragraph 0035) as it would be interpreted by one of ordinary skill in the art, examiner is interpreting the limitation “an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match” to mean at least indirectly matched contents are those contents having lower degree of similarity.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of similarity determination of contents of Evans into the feature of filtering contents of Taylor to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to use data matching using contextual analysis to enforce compliance on providing contents to users(Evans, para 0007).
But Taylor and Evans don’t explicitly teach create a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed, wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and display the filtered webpage to the user.
However, in the same field of endeavor of removal of unwanted contents from web pages Beukema teaches create a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed; and display the filtered webpage to the user(Beukema, Fig. 1 and para 0023 discloses blank space created due to deletion of contents from a webpage is retained i.e. place for removed content 122 and 128 are preserved as blank in the update page (image on the right) “irrespective of the number of search results that are removed from the search results list or the criteria upon which the search results may be displayed on a particular page, the remaining search results retain their place in the order of arrangement. While a gap between search results 124, 128 is displayed in FIG. 1……” ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of filtering contents and preserving blanks created by content removal at the browser display of Beukema into extraction of users’ preferences for filtering web contents of Taylor and Evans to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to ensure displayed contents’ arrangement order for facilitating user browsing experiences(Beukema, para 0002-0003).
But Taylor, Evans and Beukema don’t explicitly teach wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location;
However, in the same field of endeavor of blocking/unblocking of unwanted contents from web pages Maycock teaches wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content(Maycock, element 140 of Fig. 3B discloses a filtered page with a blank space 140 indicating removed content), and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location(Maycock, Fig. 3A-B and para 0083-0084 discloses users’ having an option to reinstate the blocked content at a specified blank space for viewing by using a selectable control such as a button “the graphical element display may replace the empty area of the filtered content with another social media notification…….if Jane Smith 130 tries to send or share a naked photo or sends a message of bullying content, the filter application may take the Jane Smith 130 post out of the social media feed, or the filter program may block the object, and replace the data with a graphic, notification, button, backed out area, etc., indicating filtered or blocked content”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of having an option for hiding and unhiding content on web-pages Maycock into extraction of users’ preferences for filtering web contents of Taylor, Evans and Beukema to produce an expected result of having an option to view blocked contents. The modification would be obvious because one of ordinary skill in the art would be motivated to implement an option on the webpage/display to enforce parental control for inappropriate contents(Maycock, para 0083).
Regarding claim 2(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 1 and Taylor further teaches wherein the system operates fully on a user device (Taylor, Fig. 3 discloses that filter system is running on web-browser of user computing device ).
Regarding claim 3, (Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 1 and Taylor further teaches wherein the web browser add-on is installed on a web browser in a user device (Taylor, para 0040 discloses that content filter can be implemented as browser plug-in “A web page processing 350 is provided in the form of a plug-in to the web browser. The web page processing 350 receives the web page 305 and the context information preferences 306”).
Regarding claim 5(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 1 and Evans further teaches wherein the determination of one or more matches between the extracted content and one or more of the one or more user dislikes includes an analysis of the extracted content for natural language and context (Evans, para 0156 teaches contextual understanding of any extracted contents (parsed) by natural language processing “Feature extraction controller 1522 may include a neural network data model configured to predict (e.g., extract) contextual or related text terms based on generation of vectors (e.g., word vectors) with which to determine degrees of similarity ….. feature extraction controller 1522 may be configured to implement a “word2vec” natural language processing algorithm”; where Taylor disclose a saved content preferences (likes/dislikes)).
Regarding claim 6(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 5 and Evans further teaches wherein the language and context of the extracted content are parsed for specific words that match any of the one or more user dislikes(Evans, para 0092 discloses a specific word/name can be detected “moderation processor 674 may be configured to detect a noncompliant message attribute, such as a typographical error or a profane word”).
Regarding claim 7(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 6 and Evans further teaches wherein the determination of one or more matches between the extracted content and one or more of the one or more user dislikes also considers one or more tangential relationships between the parsed language and context of the extracted content and the one or more user dislikes(Evans, para 0158 discloses determination of semantic/contextual similarity by their degree of similarity; lower degree or indirect match suggests tangential relationship “algorithms configured to determine a degree of similarity, such as an algorithm configured to implement a cosine similarity algorithm (or equivalent) to identify a measure of similarity between data (e.g., vectors) representing text data (e.g., text- based data 1505 or extracted feature data 1503) and/or image data of supplemental data 1504” ).
Regarding Claim 11(Currently Amended), Taylor teaches A method of active web-based content filtering, comprising (Taylor, Fig.3 and para 0028 discloses web-based content filtering system “The scanning may parse the contents of the web page for possible matches to the search term filtered by the contextual information”: intercepting, by a processor, an incoming webpage before reaching a web browser of the user device and prior to display on the interactive user interface, the incoming webpage based on a user input (Taylor, Fig. 3 and para 0053 disclose a web-based content filter that intercepts content requests “As soon as the results page is selected, the described post-search plug-in intercepts that page and begins scanning its contents in preparation for constructing a new header that will precis the most relevant parts of the page…”);
requesting, over a network, a user restrictions file from a backend server, the user restrictions file comprising one or more user dislikes; receiving, by the processor, the user restrictions file; extracting the one or more user restrictions and/or dislikes from the user restrictions file(Taylor, element 314 of Fig. 3 and para 0040 disclose extracting/obtaining from content preferences storage (likes/dislikes or restriction file) “The web browser session 360 includes access to context information preferences 314 that are stored for the user providing preferences of the context information that they want to apply when accessing web page content”);
determining, by the processor, undesired incoming webpage display content by comparing each of the extracted user restrictions and dislikes with the parsed display content from the incoming webpage to determine if each user restriction or dislike directly or indirectly matches the extracted content(Taylor, para 0028 content is being parsed as per user’s preferences (likes/dislikes) for filtering web contents to be displayed “The scanning may parse the contents of the web page for possible matches to the search term filtered by the contextual information”),
But Taylor does not explicitly teach parsing, by the processor, display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content; and displaying, by the processor, the filtered webpage to the user
where a direct match relies on similarity of a group comprising words and
images, and an indirect match is based on lexical semantics with at least one
degree of logical separation from a direct match, wherein the at least one degree
of logical separation leads from an extracted user restriction or dislike to parsed
content from the incoming webpage that is different from the extracted user
restriction or dislike but is related through a logic path with at least one logical
step; creating, by the processor, a filtered webpage comprising: removal of the
undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed, wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and displaying, by the processor, the filtered webpage to the user.
However, in the same field of endeavor of performing contextual semantic analysis of words and images Evans teaches parsing, by the processor, display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content (Evans, para 0156 teaches contextual understanding of any extracted contents (parsed) by natural language processing “Feature extraction controller 1522 may include a neural network data model configured to predict (e.g., extract) contextual or related text terms based on generation of vectors (e.g., word vectors) with which to determine degrees of similarity….. feature extraction controller 1522 may be configured to implement a “word2vec” natural language processing algorithm”);
where a direct match relies on similarity of a group comprising words and
images, and an indirect match is based on lexical semantics with at least one
degree of logical separation from a direct match, wherein the at least one degree
of logical separation leads from an extracted user restriction or dislike to parsed
content from the incoming webpage that is different from the extracted user
restriction or dislike but is related through a logic path with at least one logical
step (Evans, para 0158 discloses matching data such as words or images to find the
degree of similarity, here the degree of similarity suggests direct or indirect matching or degree of logical separation for matching “data representing a portion of an electronic message may be correlated to match at least one subset of disposition metrics to form a correlation data value, …. … algorithms configured to determine a degree of similarity, such as an algorithm configured to implement a cosine similarity algorithm (or equivalent) to identify a measure of similarity between data (e.g., vectors) representing text data (e.g., text-based data 1505 or extracted feature data 1503) and/or image data of supplemental data 1504”; where prior art Taylor teaches restriction data and parsed contents);
Using the broadest reasonable interpretation consistent with the specification (paragraph 0035) as it would be interpreted by one of ordinary skill in the art, examiner is interpreting the limitation “an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match” to mean at least indirectly matched contents are those contents having lower degree of similarity.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of similarity determination of contents of Evans into the feature of filtering contents of Taylor to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to use data matching using contextual analysis to enforce compliance on providing contents to users(Evans, para 0007).
But Taylor and Evans don’t explicitly teach creating, by the processor, a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed, wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and displaying, by the processor, the filtered webpage to the user.
However, in the same field of endeavor of removal of unwanted contents from web pages Beukema teaches creating, by the processor, a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed; and displaying, by the processor, the filtered webpage to the user(Beukema, Fig. 1 and para 0023 discloses blank space created due to deletion of contents from a webpage is retained i.e. place for removed content 122 and 128 are preserved as blank in the update page (image on the right) “irrespective of the number of search results that are removed from the search results list or the criteria upon which the search results may be displayed on a particular page, the remaining search results retain their place in the order of arrangement. While a gap between search results 124, 128 is displayed in FIG. 1……” ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of filtering contents and preserving blanks created by content removal at the browser display of Beukema into extraction of users’ preferences for filtering web contents of Taylor and Evans to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to ensure displayed contents’ arrangement order for facilitating user browsing experiences(Beukema, para 0002-0003).
But Taylor, Evans and Beukema don’t explicitly teach wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location.
However, in the same field of endeavor of blocking/unblocking of unwanted contents from web pages Maycock teaches wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content(Maycock, element 140 of Fig. 3B discloses a filtered page with a blank space 140 indicating removed content), and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location (Maycock, Fig. 3A-B and para 0083-0084 discloses users’ having an option to reinstate the blocked content on the blank space for viewing by using a selectable control such as a button “the graphical element display may replace the empty area of the filtered content with another social media notification…….if Jane Smith 130 tries to send or share a naked photo or sends a message of bullying content, the filter application may take the Jane Smith 130 post out of the social media feed, or the filter program may block the object, and replace the data with a graphic, notification, button, backed out area, etc., indicating filtered or blocked content”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of having an option for hiding and unhiding content on display of Maycock into extraction of users’ preferences for filtering web contents of Taylor, Evans and Beukema to produce an expected result of having an option to view blocked contents. The modification would be obvious because one of ordinary skill in the art would be motivated to implement an option on the webpage/display to enforce parental control for inappropriate contents(Maycock, para 0083).
Regarding claim 12(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 11 and Taylor further teaches wherein the method operates fully on a user device (Taylor, Fig. 3 discloses that filter system is running on web-browser of user computing device).
Regarding claim 14(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 11 and Evans further teaches wherein the determination of one or more matches between the extracted content and one or more of the one or more user dislikes includes an analysis of the extracted content for natural language and context (Evans, para 0156 teaches contextual understanding of any extracted contents (parsed) by natural language processing “Feature extraction controller 1522 may include a neural network data model configured to predict (e.g., extract) contextual or related text terms based on generation of vectors (e.g., word vectors) with which to determine degrees of similarity ….. feature extraction controller 1522 may be configured to implement a “word2vec” natural language processing algorithm”; where Taylor disclose a saved content preferences (likes/dislikes)).
Regarding claim 15(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 14 and Evans further teaches wherein the language and context of the extracted content are parsed for specific words that match any of the one or more user dislikes(Evans, para 0092 discloses a specific word/name can be detected “moderation processor 674 may be configured to detect a noncompliant message attribute, such as a typographical error or a profane word”).
Regarding claim 16(Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 15 and Evans further teaches wherein the determination of one or more matches between the extracted content and one or more of the one or more user dislikes also considers one or more tangential relationships between the parsed language and context of the extracted content and the one or more user dislikes (Evans, para 0158 discloses determination of semantic/contextual similarity by their degree of similarity; lower degree or indirect match suggests tangential relationship “algorithms configured to determine a degree of similarity, such as an algorithm configured to implement a cosine similarity algorithm (or equivalent) to identify a measure of similarity between data (e.g., vectors) representing text data (e.g., text- based data 1505 or extracted feature data 1503) and/or image data of supplemental data 1504” ).
Regarding Claim 20(Currently Amended), Taylor teaches A computer- readable non-transitory medium comprising computer- executable instructions that, when executed by at least one processor, perform procedures comprising(Taylor, Fig. 5 discloses processor and memory for executing instructions): intercepting, by a processor, an incoming webpage before reaching a web browser of the user device and prior to display on the interactive user interface, the incoming webpage based on a user input (Taylor, Fig. 3 and para 0053 disclose a web-based content filter that intercepts content requests “As soon as the results page is selected, the described post-search plug-in intercepts that page and begins scanning its contents in preparation for constructing a new header that will precis the most relevant parts of the page…”);
requesting, over a network, a user restrictions file from a backend server, the user restrictions file comprising one or more user dislikes; receiving, by the processor, the user restrictions file; extracting the one or more user restrictions and/or dislikes from the user restrictions file (Taylor, element 314 of Fig. 3 and para 0040 disclose extracting/obtaining from content preferences storage (likes/dislikes or restriction file) “The web browser session 360 includes access to context information preferences 314 that are stored for the user providing preferences of the context information that they want to apply when accessing web page content”);
determining, by the processor, undesired incoming webpage display content by comparing each of the extracted user restrictions and dislikes with the parsed display content from the incoming webpage to determine if each user restriction or dislike directly or indirectly matches the extracted content (Taylor, para 0028 content is being parsed as per user’s preferences (likes/dislikes) for filtering web contents to be displayed “The scanning may parse the contents of the web page for possible matches to the search term filtered by the contextual information”),
Taylor does not explicitly teach parsing, by the processor, display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content; where a direct match relies on similarity of a group comprising words and images, and an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match, wherein the at least one degree of logical separation leads from an extracted user restriction or dislike to parsed content from the incoming webpage that is different from the extracted user restriction or dislike but is related through a logic path with at least one logical step; creating, by the processor, a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed , wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and displaying, by the processor, the filtered webpage to the user.
However, in the same field of endeavor of performing contextual semantic analysis of words and images Evans teaches parsing, by the processor, display content from the incoming webpage using natural language processing and a semantics engine to derive understanding and context from the parsed content (Evans, para 0156 teaches contextual understanding of any extracted contents (parsed) by natural language processing “Feature extraction controller 1522 may include a neural network data model configured to predict (e.g., extract) contextual or related text terms based on generation of vectors (e.g., word vectors) with which to determine degrees of similarity….. feature extraction controller 1522 may be configured to implement a “word2vec” natural language processing algorithm”); where a direct match relies on similarity of a group comprising words and images, and an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match, wherein the at least one degree of logical separation leads from an extracted user restriction or dislike to parsed content from the incoming webpage that is different from the extracted user restriction or dislike but is related through a logic path with at least one logical step (Evans, para 0158 discloses matching data such as words or images to find the degree of similarity, here the degree of similarity suggests direct or indirect matching or degree of logical separation for matching “data representing a portion of an electronic message may be correlated to match at least one subset of disposition metrics to form a correlation data value, …. … algorithms configured to determine a degree of similarity, such as an algorithm configured to implement a cosine similarity algorithm (or equivalent) to identify a measure of similarity between data (e.g., vectors) representing text data (e.g., text-based data 1505 or extracted feature data 1503) and/or image data of supplemental data 1504”; where prior art Taylor teaches restriction data and parsed contents);
Using the broadest reasonable interpretation consistent with the specification (paragraph 0035) as it would be interpreted by one of ordinary skill in the art, examiner is interpreting the limitation “an indirect match is based on lexical semantics with at least one degree of logical separation from a direct match” to mean at least indirectly matched contents are those contents having lower degree of similarity.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of similarity determination of contents of Evans into the feature of filtering contents of Taylor to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to use data matching using contextual analysis to enforce compliance on providing contents to users(Evans, para 0007).
But Taylor and Evans don’t explicitly teach creating, by the processor, a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed, wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location; and displaying, by the processor, the filtered webpage to the user.
However, in the same field of endeavor of removal of unwanted contents from web pages Beukema teaches creating, by the processor, a filtered webpage comprising: removal of the undesired incoming webpage content and retention of blank spaces where undesired incoming website content was removed; and displaying, by the processor, the filtered webpage to the user (Beukema, Fig. 1 and para 0023 discloses blank space created due to deletion of contents from a webpage is retained i.e. place for removed content 122 and 128 are preserved as blank in the update page (image on the right) “irrespective of the number of search results that are removed from the search results list or the criteria upon which the search results may be displayed on a particular page, the remaining search results retain their place in the order of arrangement. While a gap between search results 124, 128 is displayed in FIG. 1……” ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of filtering contents and preserving blanks created by content removal at the browser display of Beukema into extraction of users’ preferences for filtering web contents of Taylor and Evans to produce an expected result of delivering user preferred contents only. The modification would be obvious because one of ordinary skill in the art would be motivated to ensure displayed contents’ arrangement order for facilitating user browsing experiences(Beukema, para 0002-0003).
But Taylor, Evans and Beukema don’t explicitly teach wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content, and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location.
However, in the same field of endeavor of blocking/unblocking of unwanted contents from web pages Maycock teaches wherein the filtered webpage is displayed with the blank spaces visually indicating the location of removed content(Maycock, element 140 of Fig. 3B discloses a filtered page with a blank space 140 indicating removed content), and wherein an option to reinstate the undesired incoming website content comprises a user-selectable control positioned within each blank space that, when activated, causes the corresponding undesired content to be displayed in that specific blank space location(Maycock, Fig. 3A-B and para 0083-0084 discloses users’ having an option to reinstate the blocked content at a specific blank space for viewing by using a selectable control such as a button “the graphical element display may replace the empty area of the filtered content with another social media notification…….if Jane Smith 130 tries to send or share a naked photo or sends a message of bullying content, the filter application may take the Jane Smith 130 post out of the social media feed, or the filter program may block the object, and replace the data with a graphic, notification, button, backed out area, etc., indicating filtered or blocked content”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of having an option for hiding and unhiding content on web-pages Maycock into extraction of users’ preferences for filtering web contents of Taylor, Evans and Beukema to produce an expected result of having an option to view blocked contents. The modification would be obvious because one of ordinary skill in the art would be motivated to implement an option on the webpage/display to enforce parental control for inappropriate contents(Maycock, para 0083).
Claim 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Taylor, Paulet et al (PGPUB Document No. 20230252099), hereafter referred as to “Taylor”, in view of Evans, David (PGPUB Document No.20220353226), hereafter, referred to as “Evans”, in view of Beukema, Peter (PGPUB Document No. 20230046572), hereafter, referred to as “Beukema”, in view of Maycock; Rena (PGPUB Document No. 20180349502), hereafter, referred to as “Maycock”, in further view of Zionpour, Ron et al (PGPUB Document No. 20220222431), hereafter, referred to as “Zionpour”.
Regarding claim 4 (Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 1 but they don’t explicitly teach wherein the extracted content comprises information about one or more goods or services.
However, in the same field of endeavor of performing semantic analysis of web pages Zionpour teaches wherein the extracted content comprises information about one or more goods or services(Zionpour, para 0147 discloses that service information such as service name can be parsed and extracted “at least one processor may determine (e.g., by parsing data according to a URL-based rule) an identifier that satisfies a parameter of a URL-based rule, such as an identifier of an individual (e.g., a name); an identifier of an activity (e.g., a flight number, tracking number, receipt number, project name, service name)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of word and context matching for comparing two sets of data related to service of Zionpour into filtering disliked contents of Taylor, Evans, Beukema and Maycock to produce an expected result of identify disliked web contents of users. The modification would be obvious because one of ordinary skill in the art would be motivated to implement natural language processing to find semantic interpretation of web contents to obtain closer matching of terms(Zionpour, para 0149).
Regarding claim 13 (Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 11 but they don’t explicitly teach wherein the extracted content comprises information about one or more goods or services.
However, in the same field of endeavor of performing semantic analysis of web pages Zionpour teaches wherein the extracted content comprises information about one or more goods or services (Zionpour, para 0147 discloses that service information such as service name can be parsed and extracted “at least one processor may determine (e.g., by parsing data according to a URL-based rule) an identifier that satisfies a parameter of a URL-based rule, such as an identifier of an individual (e.g., a name); an identifier of an activity (e.g., a flight number, tracking number, receipt number, project name, service name)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of word and context matching for comparing two sets of data related to service of Zionpour into filtering disliked contents of Taylor, Evans, Beukema and Maycock to produce an expected result of identity disliked web contents. The modification would be obvious because one of ordinary skill in the art would be motivated to implement natural language processing to find semantic interpretation of web contents to obtain closer matching of terms (Zionpour, para 0149).
Claim 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Taylor, Paulet et al (PGPUB Document No. 20230252099), hereafter referred as to “Taylor”, in view of Evans, David (PGPUB Document No.20220353226), hereafter, referred to as “Evans”, in view of Beukema, Peter (PGPUB Document No. 20230046572), hereafter, referred to as “Beukema”, in view of Maycock; Rena (PGPUB Document No. 20180349502), hereafter, referred to as “Maycock”, in further view of Dyor, Graham et al (PGPUB Document No. 20170004332), hereafter, referred to as “Dyor”.
Regarding claim 8 (Original), Taylor, Evans, Beukema and Maycock teach all the limitations of claim 1 but don’t explicitly teach wherein the user restrictions file is based, at least in part, on one or more historical user transactions.
However, in the same field of endeavor of content filtering Dyor teaches wherein the user restrictions file is based, at least in part, on one or more historical user transactions(Dyor, para 0050 discloses user restriction/dislike can be based on previous transaction/interactions “the trusted entity may obtain preferences from the user by the user's interactions with the search engine functionality of the trusted entity. The preference may be obtained by deduction, assumption, omission or other strategies”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of getting preferences from historical user interaction of Dyor into filtering disliked contents of Taylor, Evans, Beukema and Maycock to produce an expected result of identifying disliked web contents by user interactions. The modification would be obvious because one of ordinary skill in the art would be motivated to suggest personalized contents to users without violating users’ privacy by keeping the users’ preferences secured(Dyor, para 0005-0006).
Regarding claim 17 (Original), Taylor, Evans, Beukema and Bauman teach all the limitations of claim 11 but don’t explicitly teach wherein the user restrictions file is based, at least in part, on one or more historical user transactions.
However, in the same field of endeavor of content filtering Dyor teaches wherein the user restrictions file is based, at least in part, on one or more historical user transactions(Dyor, para 0050 discloses user restriction/dislike can be based on previous transaction/interactions “the trusted entity may obtain preferences from the user by the user's interactions with the search engine functionality of the trusted entity. The preference may be obtained by deduction, assumption, omission or other strategies”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of getting preferences from historical user interaction of Dyor into filtering disliked contents of Taylor, Evans, Beukema and Bauman to produce an expected result of identifying disliked web contents by user interactions. The modification would be obvious because one of ordinary skill in the art would be motivated to suggest personalized contents to users without violating users’ privacy by keeping the users’ preferences secured(Dyor, para 0005-0006).
Claim 9-10 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Taylor, Paulet et al (PGPUB Document No. 20230252099), hereafter referred as to “Taylor”, in view of Evans, David (PGPUB Document No.20220353226), hereafter, referred to as “Evans”, in view of Beukema, Peter (PGPUB Document No. 20230046572), hereafter, referred to as “Beukema”, in view of Maycock; Rena (PGPUB Document No. 20180349502), hereafter, referred to as “Maycock”, in view of Dyor, Graham et al (PGPUB Document No. 20170004332), hereafter, referred to as “Dyor”, in further view of Liu, Yinyin et al (PGPUB Document No. 20210326780), hereafter, referred to as “Liu”.
Regarding claim 9(Original), Taylor, Evans, Beukema, Maycock and Dyor teach all the limitations of claim 8 but don’t explicitly teach further comprising: a predictive model, wherein the predictive model is configured to dynamically update the user restrictions file by evaluating a plurality of relationships for one or more products based on the historical user transactions and user-stated dislikes in order to predict at least one additional user dislike.
However, in the same field of endeavor of predicting user preference Liu teaches further comprising: a predictive model, wherein the predictive model is configured to dynamically update the user restrictions file by evaluating a plurality of relationships for one or more products based on the historical user transactions and user-stated dislikes in order to predict at least one additional user dislike (Liu, para 0067-0068 disclose updating a user preference predictive model using user’s interaction for recommending a product (hotel rental) “a recommendation system that uses a set of feature representations for a hotel and the model will learn to predict whether it matches user's preference through user's interactions including user selection, search queries, and booking events”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of predicting user preference of Liu into generation of preference list of Taylor, Evans, Beukema, Maycock and Dyor to produce an expected result of adding new preferences to dislike/preference list. The modification would be obvious because one of ordinary skill in the art would be motivated to improve personalization of contents by considering users’ negative feedback interactions in selecting contents (Liu, para 0073).
Regarding claim 10 (Original), Taylor, Evans, Beukema, Maycock, Dyor and Liu teach all the limitations of claim 9 and Liu further teaches wherein the predictive model is updated based on feedback from the user input and one or more user interactions with the filtered webpage (Liu, para 0067-0068 disclose getting users feedback/selections & interactions are getting incorporated to users preference “predict whether it matches user's preference through user's interactions including user selection, search queries, and booking events”).
Regarding claim 18(Original), Taylor, Evans, Beukema, Maycock and Dyor teach all the limitations of claim 17 but don’t explicitly teach further comprising: dynamically updating, via a predictive model, the user restrictions file by evaluating a plurality of relationships for one or more products based on the historical user transactions and user-stated dislikes in order to predict at least one additional user dislike.
However, in the same field of endeavor of predicting user preference Liu teaches
further comprising: dynamically updating, via a predictive model, the user
restrictions file by evaluating a plurality of relationships for one or more products based on the historical user transactions and user-stated dislikes in order to predict at least one additional user dislike (Liu, para 0067-0068 discloses updating a user preference predictive model using user’s interaction for recommending a product (hotel rental) “a recommendation system that uses a set of feature representations for a hotel and the model will learn to predict whether it matches user's preference through user's interactions including user selection, search queries, and booking events”; where Dyor teaches preference can be dislikes);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of predicting user preference of Liu into generation of preference list of Taylor, Evans, Beukema, Maycock and Dyor to produce an expected result of adding new preferences to dislike/preference list. The modification would be obvious because one of ordinary skill in the art would be motivated to improve personalization of contents by considering users’ negative feedback interactions in selecting contents (Liu, para 0073).
Regarding claim 19 (Original), Taylor, Evans, Beukema, Maycock, Dyor and Liu teach all the limitations of claim 18 and Liu further teaches wherein the predictive model is updated based on feedback from the user input and one or more user interactions with the filtered webpage (Liu, para 0067-0068 disclose getting users feedback/selections & interactions are getting incorporated to users preference “predict whether it matches user's preference through user's interactions including user selection, search queries, and booking events”).
Response to Arguments
I. 35 U.S.C §103
Applicant’s arguments filed on 12/24/2025 have been fully considered but are
moot because the independent claim 1, 11 and 20 have been amended with newly added features which applicant’s arguments are directed towards. Since claims have been amended with new features, a new ground of rejection is presented.
Conclusion
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/ABDULLAH A DAUD/Examiner, Art Unit 2164 /AMY NG/Supervisory Patent Examiner, Art Unit 2164