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 .
Status of Claims
This action is in response to amendment filed on 1 January 2026. Claims 1, 2, 11, and 12 have been amended. Claims 1-20 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 27 January 2026 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Step 1: The claims 1-10 are a method and claims 11-20 are a system. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1-20, 22 and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A-Prong 1: independent claims (1 and 11) recite identifying one or more contextual webpage having internet content having a corresponding context score indicating a probability of co-occurrence of the one or more context terms in the internet content and a frequency of occurrence in one or more data streams from server and context score of each contextual webpage satisfying a threshold context score; selecting from the plurlity of webpages to store within a cache database on the frequency of occurrence corresponding to each contextual webpage satisfying a threshold frequency score, wherein the cache database is a subset of the corpus database; generating campaign data comprising the one or more contextual webpages stored in the cache database and during the real-time automated selection process, receiving data stream including a candidate webpage having candidate internet content ; determining a placement score for the candidate webpage incited a degree of match between the candidate internet content and the webpage of the one or more webpages within the cache database, wherein any contextual webpage in the corpus database that is not in the cache database is excluded; and transmitting, by the computer to the RTB server, an identifier of the candidate webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for selection from the one or more contextual webpages during the real-time automated selection process. These steps are considered to be fundamental economic practices and methods of organizing human activity, which are an examples of abstract ideas. These limitations fall within “Certain Methods Of Organizing Human Activity” for commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors. Simply put, these limitation merely describe standard data manipulation techniques for specifying context for placement of advertisement, which is clearly a business arrangement in its purest form. Claims 2-10 and 12-20, merely provide additional abstract concepts and narrow the abstract idea of claim 1 and 11. Further, claims 1-20, are recited at such a high level that the claimed steps amount to no more than a mental processes, such as concepts performed in the human mind (including an observation, evaluation, judgment, opinion) because a human can select content that meets a specified criteria, acknowledge an agreement to promote content that satisfying a bid threshold. That is other than reciting “by a computer “ , nothing in the claim precludes both the identifying and determining steps from practically being performed in the human mind. For example , but for “by a computer” language the claims encompasses the user thinking that the most co-occurrence of the one or more context term the highest scored terms. Thus, the limitation is a mental process.
Step 2A-Prong 2: The claims recite additional elements: a computer user to perform the obtaining, identifying, generating, receiving, deteriming and transmitting steps. The computer in these steps is recited at a high level of generality i.e., as a generic computer performing a generic computer functions of processing data (scoring of probability of co-occurrence of the context terms). Obtaining from client device via user interface, generating data, receiving a bidstream from an RTB server , and transmitting to the RTB an identifier. The obtaining, receiving and transmitting limitation are also reacted at a high level of gentility ( i.e., , as a general means of gathering data for use in the identifying, generating and determining steps), and amount to mere data gathering, which is a form of insignificant extra-solution activity. The, the user device , interface, the server and cache database are also recited at a high-level of generality (i.e., the user device via the interface for performing input data, the sever the database also used of storing data). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (the computer, user device, the interface, server and database ). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B: As discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claim is ineligible.
Further, the courts have consistently recognized that merely presenting the results of
abstract processes of collecting and analyzing information, without more (such as identifying a
particular tool for presentation), is abstract as an ancillary part of such collection and analysis.
See, e.g., Content Extraction, 776 F.3d at 1347; Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709,
715 (Fed. Cir. 2014). Examiner asserts that the claim's use of data streams, calculations, and determinations is standard data processing. The steps of finding matching content, calculating a score, and transmitting data are routine functions performed by generic computers ” thus it offers no more than presenting anything that includes the content that resulted from data manipulation.
In sum, the combination of steps that obtaining, identifying, selecting, receiving and transmitting and stores a record are at best is doing no more than generally linking the claims to network environment that sends and receives communications– see MPEP 2106.05(h). See also, OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network).
TLI Communications provides an example of a claim invoking computers and other
machinery merely as a tool to perform an existing process. The court stated that the claims
describe steps of recording, administration and archiving of digital images, and found them to be
directed to the abstract idea of classifying and storing digital images in an organized manner. 823
F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of
performing these functions using a telephone unit and a server and noted that these elements
were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and
operate as a digital camera including compressing images and transmitting those images, and the
server simply receives data, extracts classification information from the received data, and stores
the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at
1747-48.
Dependent claims 2-10 and 12-20, these claims recite limitation that further define the same abstract idea noted in claims 1 and 11, therefore, they are considered patent ineligible for the dame reason as above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Henkin et al (US Pub., No., 2011/0213655 A1) in view of Freeman et al (US Pub., 2012/0066359 A1)
With respect to claim 1, Henkin teaches a computer-implemented method for more efficiently selecting from a reduced dataset during a real-time automated selection process for loading content on a webpage ( paragraph [0051], discloses methods, systems, and computer program product for facilitating on-line contextual advertising operations.. and paragraph [1802], discloses MapReduce may be applied to significantly larger dataset ) , the method comprising:
prior to a real-time automated selection process(paragraph [0051], discloses real-time analysis ) ,
obtaining, by a computer, one or more context terms from a client device via a user interface( Fig. 8, 811, discloses enter keyword, search [obtain one or more context term], paragraph [0063], dislcies webpage obtained from client computer system, );
identifying, by the computer, a plurality of contextual webpages having internet content stored in a corpus database (Fig. 2, 204 discloses store corpus (int corpus database )of webpage data or webpages or documents on the order of hundreds of millions of documents, paragraph [0016], discloses dynamic taxonomy databased and/or Related Content corpus , paragraph [0138], discloses analyzing selected webpages or other documents which have been identified for contextual analysis, bank end 250 may include a queue of URLs corrosinding to webpages (or other document) to be analyzed and paragraph [0153], discloses Dynamic Taxonomy Database (DTD) (e.g., organized by topic), paragraphs [0163], [0166], discloses representation of Dynamic Taxonomy Database, Related Content Corus, Index, ) , each contextual webpage having a corresponding context score indicating a probability of co-occurrence of the one or more context terms in the internet content and a frequency of occurrence of each contextual webpage in one or more data strem from a server the context score of each contextual webpage satisfying a threshold context score (paragraph [0052], discloses the statistical distribution of word and phrase of the web page may be determined and scored against a taxonomy of topics stored in a database on the server.., a score indicting how related the web page is to each topic in the taxonomy is determined.., paragraph [0053], discloses occurrence of keywords/key phrase on the page that relate to each topic.., paragraph [0056], discloses a statistical distribution of the occurrences of the key phrase or phrase across the topics in the taxonomy…, the web pages are analyzed the count (the occurrences of the key phrase or phrase in each topic) may be dynamically updated …, paragraph [0057], discloses determine whether to use a particular key phrases or phrase, paragraph [0063], dislcies pages can then be scored against the sports topic based on the occurrence of that key phrase and the relative correlation of the key phrase to the topic of sport, paragraph [0141], discloses indexer 252a which, for example, may be operable for automatically and dynamically indexing the pages, titles, topics, phrase, etc., …, indexer may be congrued or designed to facilitate or able a quick retrieval or similar page (e.g., based on TF-IDF scoring .., and paragraph [0227], discloses identifying document/content (e.g., source pages, source page content, target pages, related content advertisement, advertismetn landing pages and etc. and paragraphs [0395]-[0401], discloses respective score value may be calculates for each word/phrase identified in the source document according to: Score (phrase-page) = a*Frequency +b *Tittle c*MCB + d *Link, where :…);
selecting, by the computer from the plurality of contextual webpage identified within the corpus database , a reduced set of contextual webpages to store within a cache databased based on the frequency of occurrence corresponding to each contextual webpage satisfying a threshold frequency score, wherein the cache database is a subset of the corpus database (paragraph [0063], discloses pages can then be scored against the sports topic based on the occurrence of the key phrase and the relative correlation of that key phrase to the topic of sports, page related to sports can then be selected and linked to one another based on this key phrase (and other words/phrases appearing on the pages, paragraph [0110], discloses cache/index/repository system, and paragraph [0137], discloses caching or storing selected Key Phrase ..))) and stores the reduced set of contextual webpages configured to be accessed during the real-time automated selection process(paragraphs [0488]-[0499], discloses indexing and/or scoring properties .., a respective relevance sore..) ; and
generating, by the computer, campaign data comprising the one or more contextual webpages stored in the cache database(Fig. 64H, discloses Campaign name, CPM, daily budget, categories [campaign data], Fig. 66E, discloses create campaign Wizard: set camping , Fig. 98, 195 discloses ad campaign’s creatives components ) ; and
during the real-time automated selection process(paragraph [0113], discloses autotmcially and dynamically adapted, in real-time, its algorithms and or other mechanisms for selecting and/or estimating potential revenue relating to one-line contextual advertising techniques );
receiving, by the computer, a bidstream from an RTB server, the data stream including a candidate webpage having candidate internet content(paragraph [0061], discloses candidate ads may be obtained from ad servers who bid on the ad placement opportunity, the candidate items of target content are also scored against the taxonomy, the related score of the source, key phrase and targets are determined, paragraph [0233], dislcies the Dynamic Taxonomy Database and/or related content repository for identifying and/or retrieving (e.g., in real time a substantial real-time desired content such as, for example, a potential ad candidate, potential related content candidate, potential related content and paragraph [0486], discloses identify and retrieve potential relevant ads candidates, potential related content candidates, potential related video candidates, and paragraph [0572], dislcies potential target DOL elements (e.g., related content, pages video etc.) ); and
determining, by the computer, a placement score for the candidate webpage indicating a degree of match between the candidate internet content of the of the candidate webpage against the internet content of each contextual webpage of the one or more contextual webpages within the cache database, wherein any contextual webpage in the corpus database that is not in the cache database is excluded(paragraph [0053], discloses the web pages are scored against each of the topics in the taxonomy databased on the server system.., the score for each topic may be normalized and represented by a number between 0 and 1.., the resulting list of score is a vector representing relatedness of the web page of the topics in the taxonomy database, paragraph [0061], discloses the server system determines which key phrases on the source page should be used for linking and send instructions back to browser .., paragraph [0062], discloses the taxonomy that is used for the above processing may be dynamic, .., paragraph [0063], discloses pages can be scored against the sport topic based on the occurrence of the key phrase and paragraph [0512]-[0520], discloses retravel from the index brings all (or selected ones of ) the result that pass different threshold values may be between 0-1, the default threshold example is 0.25,.., one or lore identify/score phrase option may be performed .., maximized relevancy and yield to the source the target page the score for each triplet of ..),
Henkin teaches the above elements including transmitting, by the computer to the RTB server, an identifier of the candidate webpage (paragraph [821], discloses a unique SourcePage ID for the received web page content and to transmit the source page ID, paragraph [0823], discloses webpage URL [an identifier of the candidate webpage] and paragraph [0827], discloses a SourcePage ID represent a unique identifier for a specific webpage ) , the publisher may be defined different threshold for each Ad/related elements type such as for example , one of the followings (or combination thereof): ads, video, audio, related information related content related article, etc. (see paragraphs [0500]-[0511]), the retravel from the index bring all (or selected ones of) the results the pass different threshold value for ads video and infoatmion. The thresh value maybe be between 0-1, the default threshold example is 0.25 (paragraph [0512]) and DOL related score value (paragraph [0883]). Henkin failed to explicitly teach the corrosinding transmitted SourcePage ID represent a unique identifier for a specific webpage is transmitted the webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for selection from the one or more contextual webpages during the real-time automated selection process.
However, Freeman teaches transmitting, by the computer to the RTB server, an identifier of the candidate webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for generating content for the contextual webpages during the real-time automated selection process (paragraphs [0011]-[0013], discloses counting a number of occurrence of the at least one keyword on the webpage, paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 2 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method further comprising identifying, by the computer, the bid placement webpage (paragraph [821], discloses a unique SourcePage ID for the received web page content and to transmit the source page ID, paragraph [0823], discloses webpage URL [an identifier of the candidate webpage] paragraph [0827], discloses a SourcePage ID represent a unique identifier for a specific webpage and paragraph [0898], dislcies solicit bids for advertismtn to be displayed .., of the source web page ) , candidate ads may be obtained from ad server who bid on the ad placement opportunity .., the related scores of the source, key phrase and targe are determined ..(paragraph [0061]) . Henkin failed to teach the corresponding webpage is selected based on the placement score of the candidate webpage satisfying a threshold page score.
However, Freeman teaches webpage is selected based on the placement score of the candidate webpage satisfying a threshold page score(paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 3 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method further comprising: receiving, by the computer from the [[RTB]] server, an availability list of one or more available webpages requesting bids from a [[bid]]data stream system(paragraph [0063], discloses selected webpages or set of web pages may be manually designed); and
calculating, by the computer, a real-time page score for each available webpage in an availability list based, at least in part, upon a number of occurrences of one or more campaign terms comprising one or more updated beacon terms and one or more in-context terms in the available webpage(paragraph [0063], discloses pages being analyzed).
With respect to claim 4 Henkin in view of Freeman teaches elements of claim 3, furthermore, Henkin teaches the method further comprising identifying, by the computer, a bidding list of webpages comprising each of one or more available webpages in the availability list satisfying a bid threshold(paragraph [0063], discloses analyzed designated sets of pages to the topic..).
With respect to claim 5 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method , further comprising storing, by the computer into a campaign database, the campaign data, wherein the campaign data is configured for executing a real-time automated bidding selection operation for the candidate webpage during the real-time bidding selection operation(paragraph [0108], discloses real-time insertion of textual markup objects and dynamic content, identification and selection of related content and/or related elements, dynamic generation of dynamic overlay layers (DOLs) and paragraph [0113], discloses autotmcially and dynamically adapted, in real-time, its algorithms and or other mechanisms for selecting and/or estimating potential revenue relating to one-line contextual advertising techniques ).
With respect to claim 6 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method further comprising identifying, by the computer, a plurality of groups corresponding to the placement score associated with the candidate webpage, each group in the plurality of groups based on the campaign data (paragraph [0063], discloses pages can be scored against the sport topic based on the occurrence of the key phrase and paragraph [0512]-[0520], discloses retravel from the index brings all (or selected ones of ) the result that pass different threshold values may be between 0-1, the default threshold example is 0.25,.., one or lore identify/score phrase option may be performed .., maximized relevancy and yield to the source the target page the score for each triplet of ..) .
With respect to claim 7 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method , wherein the campaign data includes at least one of in-context phrases, out-of-context phrases, and beacon phrases (paragraph [0480], discloses using the various types of input data such as, for example: source page key phrase and page topic infoatmion ad campaign infoatmion).
With respect to claim 8 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method further comprising: prior to a future bid-time real-time automated selection process: selecting, by the computer from a plurality of corpus terms stored in the corpus database, one or more beacon terms using the one or more context terms, each corpus term selected for the one or more beacon terms has a co-occurrence probability with each context term of the one or more context terms that satisfies a threshold probability(paragraph [0063], discloses pages can then be scored against the sports topic based on the occurrence of the key phrase and the relative correlation of that key phrase to the topic of sports, page related to sports can then be selected and linked to one another based on this key phrase (and other words/phrases appearing on the pages, paragraph [0110], discloses cache/index/repository system, and paragraph [0137], discloses caching or storing selected Key Phrase ..)); and
presenting, by the computer, the one or more beacon terms selected using the one or more context terms to a user via the user interface of the client device(paragraph [0934], discloses selected KeyPhrase(s) for highlight/markup which is to be displayed at the client system).
With respect to claim 9 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method1, further comprising: calculating, by the computer, a performance score to identify a likelihood of an interaction with the campaign data(paragraph [1446], discloses facility performance tracking .., and paragraph [1585], discloses score for each phrase bed on past performance ). Henkin failed to teach transmitting, by the computer, an [[bid]] indication for the candidate webpage, responsive to the performance score satisfying a threshold.
However, Freeman transmitting, by the computer, an [[bid]] indication for the candidate webpage, responsive to the performance score satisfying a threshold (paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 10 Henkin in view of Freeman teaches elements of claim 1, furthermore, Henkin teaches the method further comprising:
generating, by the computer, context data for the candidate webpage based upon user inputs received from the client device via the user interface(paragraph [0125], discloses generating contextual in-text KeyPhrase advertising for one or more selected KeyPhrase of the web page.., and paragraph [1549], disclose generating more content for the advertiser web site for better search ranking); and
transmitting, by the computer, the context data to the client device for display at the user interface(paragraph [0811], discloses transmitting or serving web page content including the tag information to the client system).
With respect to claim 11, Henkin teaches a system for more efficiently selecting from a reduced dataset during a real-time automated selection process for loading content on a webpage ( paragraph [0051], discloses methods, systems, and computer program product for facilitating on-line contextual advertising operations.. and paragraph [1802], discloses MapReduce may be applied to significantly larger dataset ) , the system comprising:
a server comprising a processor (Fig. 3G, ad server(s), Fig. 74 7403, server and paragraph [0052], discloses server on Internet by a client computing system)) configured to:
prior to a real-time automated selection process(paragraph [0051], discloses real-time analysis )
obtaining, by a computer, one or more context terms from a client device via a user interface( Fig. 8, 811, discloses enter keyword, search [obtain one or more context term], paragraph [0063], dislcies webpage obtained from client computer system, );
identifying, by the computer, a plurality of contextual webpages having internet content stored in a corpus database (Fig. 2, 204 discloses store corpus (int corpus database )of webpage data or webpages or documents on the order of hundreds of millions of documents, paragraph [0016], discloses dynamic taxonomy databased and/or Related Content corpus , paragraph [0138], discloses analyzing selected webpages or other documents which have been identified for contextual analysis, bank end 250 may include a queue of URLs corrosinding to webpages (or other document) to be analyzed and paragraph [0153], discloses Dynamic Taxonomy Database (DTD) (e.g., organized by topic), paragraphs [0163], [0166], discloses representation of Dynamic Taxonomy Database, Related Content Corus, Index, ) , each contextual webpage having a corresponding context score indicating a probability of co-occurrence of the one or more context terms in the internet content and a frequency of occurrence of each contextual webpage in one or more data strem from a server the context score of each contextual webpage satisfying a threshold context score (paragraph [0052], discloses the statistical distribution of word and phrase of the web page may be determined and scored against a taxonomy of topics stored in a database on the server.., a score indicting how related the web page is to each topic in the taxonomy is determined.., paragraph [0053], discloses occurrence of keywords/key phrase on the page that relate to each topic.., paragraph [0056], discloses a statistical distribution of the occurrences of the key phrase or phrase across the topics in the taxonomy…, the web pages are analyzed the count (the occurrences of the key phrase or phrase in each topic) may be dynamically updated …, paragraph [0057], discloses determine whether to use a particular key phrases or phrase, paragraph [0063], dislcies pages can then be scored against the sports topic based on the occurrence of that key phrase and the relative correlation of the key phrase to the topic of sport paragraph [0141], discloses indexer 252a which, for example, may be operable for automatically and dynamically indexing the pages, titles, topics, phrase, etc., …, indexer may be congrued or designed to facilitate or able a quick retrieval or similar page (e.g., based on TF-IDF scoring .., and paragraph [0227], discloses identifying document/content (e.g., source pages, source page content, target pages, related content advertisement, advertismetn landing pages and etc. and paragraphs [0395]-[0401], discloses respective score value may be calculates for each word/phrase identified in the source document according to: Score (phrase-page) = a*Frequency +b *Tittle c*MCB + d *Link, where :…);
selecting, by the computer from the plurality of contextual webpage identified within corpus database on or more contextual webpages to store within a cache databased based on the frequency of occurrence corresponding to each contextual webpage satisfying a threshold frequency score, wherein the cache database is a subset of the corpus database(paragraph [0063], discloses pages can then be scored against the sports topic based on the occurrence of the key phrase and the relative correlation of that key phrase to the topic of sports, page related to sports can then be selected and linked to one another based on this key phrase (and other words/phrases appearing on the pages, paragraph [0110], discloses cache/index/repository system, and paragraph [0137], discloses caching or storing selected Key Phrase ..))) and stores the reduced set of contextual webpages configured to be accessed during the real-time automated selection process(paragraphs [0488]-[0499], discloses indexing and/or scoring properties .., a respective relevance sore..) ; and
generating, by the computer, campaign data comprising the reduced set of one or more contextual webpages stored in the cache database(Fig. 64H, discloses Campaign name, CPM, daily budget, categories [campaign data], Fig. 66E, discloses create campaign Wizard: set camping , Fig. 98, 195 discloses ad campaign’s creatives components ) ; and
during the real-time automated selection process(paragraph [0113], discloses autotmcially and dynamically adapted, in real-time, its algorithms and or other mechanisms for selecting and/or estimating potential revenue relating to one-line contextual advertising techniques );
receiving, by the computer, a bidstream from an RTB server, the data stream including a candidate webpage having candidate internet content(paragraph [0061], discloses candidate ads may be obtained from ad servers who bid on the ad placement opportunity, the candidate items of target content are also scored against the taxonomy, the related score of the source, key phrase and targets are determined, paragraph [0233], dislcies the Dynamic Taxonomy Database and/or related content repository for identifying and/or retrieving (e.g., in real time a substantial real-time desired content such as, for example, a potential ad candidate, potential related content candidate, potential related content and paragraph [0486], discloses identify and retrieve potential relevant ads candidates, potential related content candidates, potential related video candidates, and paragraph [0572], dislcies potential target DOL elements (e.g., related content, pages video etc.) ); and
determining, by the computer, a placement score for the candidate webpage indicating a degree of match between the candidate internet content of the of the candidate webpage against the internet content of each contextual webpage of the one or more contextual webpages within the cache database, wherein any contextual webpage in the corpus database that is not in the cache database is excluded(paragraph [0053], discloses the web pages are scored against each of the topics in the taxonomy databased on the server system.., the score for each topic may be normalized and represented by a number between 0 and 1.., the resulting list of score is a vector representing relatedness of the web page of the topics in the taxonomy database, paragraph [0061], discloses the server system determines which key phrases on the source page should be used for linking and send instructions back to browser .., paragraph [0062], discloses the taxonomy that is used for the above processing may be dynamic, .., paragraph [0063], discloses pages can be scored against the sport topic based on the occurrence of the key phrase and paragraph [0512]-[0520], discloses retravel from the index brings all (or selected ones of ) the result that pass different threshold values may be between 0-1, the default threshold example is 0.25,.., one or lore identify/score phrase option may be performed .., maximized relevancy and yield to the source the target page the score for each triplet of ..),
Henkin teaches the above elements including transmitting, by the computer to the RTB server, an identifier of the candidate webpage (paragraph [821], discloses a unique SourcePage ID for the received web page content and to transmit the source page ID, paragraph [0823], discloses webpage URL [an identifier of the candidate webpage] and paragraph [0827], discloses a SourcePage ID represent a unique identifier for a specific webpage ) , the publisher may be defined different threshold for each Ad/related elements type such as for example , one of the followings (or combination thereof): ads, video, audio, related information related content related article, etc. (see paragraphs [0500]-[0511]), the retravel from the index bring all (or selected ones of) the results the pass different threshold value for ads video and infoatmion. The thresh value maybe be between 0-1, the default threshold example is 0.25 (paragraph [0512]) and DOL related score value (paragraph [0883]). Henkin failed to explicitly teach the corrosinding transmitted SourcePage ID represent a unique identifier for a specific webpage is transmitted the webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for selection from the one or more contextual webpages during the real-time automated selection process.
However, Freeman teaches transmitting, by the computer to the RTB server, an identifier of the candidate webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for selection from the one or more contextual webpages during the real-time automated selection process (paragraphs [0011]-[0013], discloses counting a number of occurrence of the at least one keyword on the webpage, paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 12 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising identifying, by the computer, the bid placement webpage (paragraph [821], discloses a unique SourcePage ID for the received web page content and to transmit the source page ID, paragraph [0823], discloses webpage URL [an identifier of the candidate webpage] , paragraph [0827], discloses a SourcePage ID represent a unique identifier for a specific webpage and paragraph [0898], dislcies solicit bids for advertismtn to be displayed .., of the source web page) , candidate ads may be obtained from ad server who bid on the ad placement opportunity .., the related scores of the source, key phrase and targe are determined ..(paragraph [0061]) . Henkin failed to teach the corresponding webpage is selected based on the placement score of the candidate webpage satisfying a threshold page score.
However, Freeman teaches webpage is selected based on the placement score of the candidate webpage satisfying a threshold page score(paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 13 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising: receiving, by the computer from the [[RTB]] server, an availability list of one or more available webpages requesting bids from a [[bid]]data stream system(paragraph [0063], discloses selected webpages or set of web pages may be manually designed); and
calculating, by the computer, a real-time page score for each available webpage in an availability list based, at least in part, upon a number of occurrences of one or more campaign terms comprising one or more updated beacon terms and one or more in-context terms in the available webpage(paragraph [0063], discloses pages being analyzed).
With respect to claim 14 Henkin in view of Freeman teaches elements of claim 13, furthermore, Henkin teaches the system further comprising identifying, by the computer, a bidding list of webpages comprising each of one or more available webpages in the availability list satisfying a bid threshold(paragraph [0063], discloses analyzed designated sets of pages to the topic..).
With respect to claim 15 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system , further comprising storing, by the computer into a campaign database, the campaign data, wherein the campaign data is configured for executing a real-time automated bidding selection operation for the candidate webpage during the real-time bidding selection operation(paragraph [0108], discloses real-time insertion of textual markup objects and dynamic content, identification and selection of related content and/or related elements, dynamic generation of dynamic overlay layers (DOLs) and paragraph [0113], discloses autotmcially and dynamically adapted, in real-time, its algorithms and or other mechanisms for selecting and/or estimating potential revenue relating to one-line contextual advertising techniques ).
With respect to claim 16 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising identifying, by the computer, a plurality of groups corresponding to the placement score associated with the candidate webpage, each group in the plurality of groups based on the campaign data (paragraph [0063], discloses pages can be scored against the sport topic based on the occurrence of the key phrase and paragraph [0512]-[0520], discloses retravel from the index brings all (or selected ones of ) the result that pass different threshold values may be between 0-1, the default threshold example is 0.25,.., one or lore identify/score phrase option may be performed .., maximized relevancy and yield to the source the target page the score for each triplet of ..) .
With respect to claim 17 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system , wherein the campaign data includes at least one of in-context phrases, out-of-context phrases, and beacon phrases (paragraph [0480], discloses using the various types of input data such as, for example: source page key phrase and page topic infoatmion ad campaign infoatmion).
With respect to claim 18 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising: prior to a future bid-time real-time automated selection process: selecting, by the computer from a plurality of corpus terms stored in the corpus database, one or more beacon terms using the one or more context terms, each corpus term selected for the one or more beacon terms has a co-occurrence probability with each context term of the one or more context terms that satisfies a threshold probability(paragraph [0063], discloses pages can then be scored against the sports topic based on the occurrence of the key phrase and the relative correlation of that key phrase to the topic of sports, page related to sports can then be selected and linked to one another based on this key phrase (and other words/phrases appearing on the pages, paragraph [0110], discloses cache/index/repository system, and paragraph [0137], discloses caching or storing selected Key Phrase ..)); and
presenting, by the computer, the one or more beacon terms selected using the one or more context terms to a user via the user interface of the client device(paragraph [0934], discloses selected KeyPhrase(s) for highlight/markup which is to be displayed at the client system).
With respect to claim 19 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising: calculating, by the computer, a performance score to identify a likelihood of an interaction with the campaign data(paragraph [1446], discloses facility performance tracking .., and paragraph [1585], discloses score for each phrase bed on past performance ). Henkin failed to teach transmitting, by the computer, an [[bid]] indication for the candidate webpage, responsive to the performance score satisfying a threshold.
However, Freeman transmitting, by the computer, an [[bid]] indication for the candidate webpage, responsive to the performance score satisfying a threshold (paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ). Therefore, it would have been obvious to the one ordinary skill in the art before the effective filing date of the claimed invention for unique identifier for a specific webpage is transmitted of Henkin with displying the result of the evaluation of one or more link-host webpage and receiving first and second identifier of webpages of Freeman in order to place advertisement on the candidate webpage (see Freeman, paragraph [0107]).
With respect to claim 20 Henkin in view of Freeman teaches elements of claim 11, furthermore, Henkin teaches the system further comprising:
generating, by the computer, context data for the candidate webpage based upon user inputs received from the client device via the user interface(paragraph [0125], discloses generating contextual in-text KeyPhrase advertising for one or more selected KeyPhrase of the web page.., and paragraph [1549], disclose generating more content for the advertiser web site for better search ranking); and
transmitting, by the computer, the context data to the client device for display at the user interface(paragraph [0811], discloses transmitting or serving web page content including the tag information to the client system).
Prior arts:
Henkin et al (US Pub., No., 2011/0213655 A1) discloses different types of Hybrid contextual advertising and related content analysis and display techniques are disclosed for facilitating on-line contextual advertising operations and related content delivery operations implemented in a computer network. At least some embodiments may be configured or designed enabling advertisers to provide contextual advertising promotions to end-users based upon real-time analysis of web page content which may be served to an end-user's computer system.
Kingman, Jr, et al (US Patent No., 10,599,009 B1) focused on the system links Internet web page context with audience usage and location data to support advertising efficiency and effectiveness. An ontology of categories is created where domains and website pages are classified and scored against the links on those pages and the meta-tag key word pools that are harvested from those web pages. An ontology of high-level categories are derived from the frequency of the key words appearing within the domain URL addresses of the pages, the domain of the links on those pages or within the content of the pages themselves.
Freeman et al (US Pub., 2012/0066359 A1) focused on a method for valuing a link-hosting webpage is provided. The method includes the act of receiving, on a computer system, at least one keyword. The method also includes the act of receiving, on a computer system, at least one identifier of a webpage, the webpage having been previously identified as a link-hosting webpage. The method also includes the act of accessing information about the webpage over a computer network.
Response to Arguments
Applicant's arguments of 35 U.S.C 101 rejection with respect to claims 1-20 filed on 27 January 2026 have been fully considered but they are not persuasive. Applicants’ arguments of as amended, the claims recite features that describe an amount of technical detail and computing functions that can only interpreted as describing as mental process or generic automation of data selection and delivery is not persuasive. As updated by the above rejections the claimed invention is not patent-eligible because it is directed to a "judicial exception," such as an abstract idea. Abstract ideas include mathematical concepts, methods of organizing human activity, and mental processes.
The described claims found to recite an abstract idea for the following reasons:
Organizing human activity: The claim describes a method for managing an advertising campaign and selecting content for real-time bidding (RTB). This falls under the category of a business method for organizing human activity, which is a recognized abstract idea.
Mathematical concepts: The steps involve determining a "context score" and a "placement score," which are mathematical concepts. While using mathematical formulas is not inherently abstract, relying on them to select web content based on co-occurrence and frequency is an abstract process.
Conventional computing: The claim describes using conventional computer components like a "server" and a "cache database" to implement the abstract idea. Simply using a generic computer to automate a business process does not make it patent-eligible.
Applicants’ arguments of forming a cache database using a large corpus databased and identifying a context score that is based on a co-occurrence of terms within contextual webpages and per-page frequency of occurrence in server data streams. Tracking the co-occurrence of terms and the frequence of occurrence of page in a plurality of data streams cannot be done by a human mind or are the claims directed to a method of organizing human activity, The PEG emphasize that a claim doss not receive a mental process with it control limitation that cannot practical be performed in human mind..” is not persuasive. The claimed limitation of “ selecting, by the computer from the plurality of contextual webpage identified within the corpus database , a reduced set of contextual webpages to store within a cache databased based on the frequency of occurrence corresponding to each contextual webpage satisfying a threshold frequency score, wherein the cache database is a subset of the corpus database and stores the reduced set of contextual webpages configured to be accessed during the real-time automated selection process” . This limitation as drafted, is processes, that, under its broadest reasonable interpretation, it convers identifying, analyzing, and storing data in a cache constitute abstract ideas, similar to organizing information or generic data manipulation.
Further, the claims lack inventive concept in step 2 when a selection and caching process use a generic computer functionality even it performs the task faster. The claims must show a specific improvement in the computer’s functioning, such as a specialized caching architecture or an innovative algorithm for frequency calculation that goes beyond conventional steps. Clams that escribe “what “ the system does (e.g., selecting a reduce set .. to store”) rather than “how” it does it through a specific technical mechanism are often deemed ineligible.
In order to overcome the 35 U.S.C 101 rejections, the claims feature focuses on
Technical Improvement: The method must be framed as a solution to a technical problem (e.g., excessive latency, limited memory) rather than a business or data management goal.
Specific Implementation: Emphasize that the "reduced set of contextual webpages" is identified through a specialized, non-conventional algorithm that enhances computer performance.
Distinguish from Conventional Caching: Arguments should focus on how this particular frequency thresholding technique is unique compared to standard caching techniques. Thus, the claims are ineligible.
Applicant' s argument relating to the Enfish are misguided. Enfish is an example of something the courts found not to be abstract. The instant Application lacks the self-referential table of Enfish which proved to the element that was determined to be non-abstract. Therefore, Enfish is not applicable to the instant case. Examiner used Alice/ Mayo two-part analysis used in the rejection above to determine that the claims are ineligible.
Applicant’s arguments of 35 U.S.C 103 rejection filed on 27 January 2026 with respect to claim(s) 1-20 have been considered but is not persuasive. Applicants’ arguments of the cited reference do not teach or suggest at least the features of “ identifying, by the computer, a plurality of contextual webpages having internet content stored in a corpus database each contextual webpage having a corresponding context score indicating a probability of co-occurrence of the one or more context terms in the internet content and a frequency of occurrence of each contextual webpage in one or more data strem from a server the context score of each contextual webpage satisfying a threshold context score is not persuasive.
Henkin teaches identifying, by the computer, a plurality of contextual webpages having internet content stored in a corpus database (Fig. 2, 204 discloses store corpus (int corpus database )of webpage data or webpages or documents on the order of hundreds of millions of documents, paragraph [0016], discloses dynamic taxonomy databased and/or Related Content corpus , paragraph [0138], discloses analyzing selected webpages or other documents which have been identified for contextual analysis, bank end 250 may include a queue of URLs corrosinding to webpages (or other document) to be analyzed and paragraph [0153], discloses Dynamic Taxonomy Database (DTD) (e.g., organized by topic), paragraphs [0163], [0166], discloses representation of Dynamic Taxonomy Database, Related Content Corus, Index, ) , each contextual webpage having a corresponding context score indicating a probability of co-occurrence of the one or more context terms in the internet content and a frequency of occurrence of each contextual webpage in one or more data strem from a server the context score of each contextual webpage satisfying a threshold context score (paragraph [0052], discloses the statistical distribution of word and phrase of the web page may be determined and scored against a taxonomy of topics stored in a database on the server.., a score indicting how related the web page is to each topic in the taxonomy is determined.., paragraph [0053], discloses occurrence of keywords/key phrase on the page that relate to each topic.., paragraph [0056], discloses a statistical distribution of the occurrences of the key phrase or phrase across the topics in the taxonomy…, the web pages are analyzed the count (the occurrences of the key phrase or phrase in each topic) may be dynamically updated …, paragraph [0057], discloses determine whether to use a particular key phrases or phrase, paragraph [0063], dislcies pages can then be scored against the sports topic based on the occurrence of that key phrase and the relative correlation of the key phrase to the topic of sport, paragraph [0141], discloses indexer 252a which, for example, may be operable for automatically and dynamically indexing the pages, titles, topics, phrase, etc., …, indexer may be congrued or designed to facilitate or able a quick retrieval or similar page (e.g., based on TF-IDF scoring .., and paragraph [0227], discloses identifying document/content (e.g., source pages, source page content, target pages, related content advertisement, advertismetn landing pages and etc. and paragraphs [0395]-[0401], discloses respective score value may be calculates for each word/phrase identified in the source document according to: Score (phrase-page) = a*Frequency +b *Tittle c*MCB + d *Link, where :…).
Applicants’ arguments of Henkin is devoid of any contemplation of a frequency of occurrence indicating a presence of contextual webpage in one or more data streams from a server is not persuasive. Henkin in paragraph [1694], describes [score- score for phrase for topic – score (frequency of appearance of phrase on page, where it appeared (URL, title, MCB) -computed by classifier during classification – corresponds to score shown of frequency, also in paragraph [0141], discloses indexer 252a which, for example, may be operable for automatically and dynamically indexing the pages, titles, topics, phrase, etc., …, indexer may be congrued or designed to facilitate or able a quick retrieval or similar page (e.g., based on TF-IDF scoring .., which inherently indicates the presence of a contextual webpage in a data stream.
Applicants’ arguments of Freeman does not include any discussion regarding a frequency of occurrence of each contextual webpage in one or more data stream from the server is not persuasive.
While, Henkin teaches the elements cited above, Freeman reference combine to address the limitation of transmitting, by the computer to the RTB server, an identifier of the candidate webpage having the placement score satisfying a bid threshold score, wherein the identifier of the candidate webpage is configured for selection from the one or more contextual webpages during the real-time automated selection process (paragraphs [0011]-[0013], discloses counting a number of occurrence of the at least one keyword on the webpage, paragraph [0015], discloses generating a quantitative importance score for the web page, paragraph [0020], discloses receiving a first identifier of a first webpage and a second identifier of a second webpage paragraph [0045], discloses an identifier of the webpage, and paragraph [0092], discloses select the candidate webpage from the list ).
Furthermore, Freeman in paragraph [0088] teaches the database 208 may also be configured to store a competitor list that identifies the webpage(s) of one or more competitors of the marketers. Thus, the combination of Henkin and Freeman address the claimed limitation.
Conclusion
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/SABA DAGNEW/Primary Examiner, Art Unit 3621
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