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 C.F.R. § 1.114
A request for continued examination under 37 C.F.R. § 1.114, including the fee set forth in 37 C.F.R. § 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 C.F.R. § 1.114, and the fee set forth in 37 C.F.R. § 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 C.F.R. § 1.114. Applicant's submission filed on February 18, 2026 has been entered.
All claims are identical to or patentably indistinct from, or have unity of invention with claims in the application prior to the entry of the submission under 37 C.F.R. § 1.114 (that is, restriction (including a lack of unity of invention) would not be proper) and all claims could have been finally rejected on the grounds and art of record in the next Office action if they had been entered in the application prior to entry under 37 C.F.R. § 1.114. Accordingly, THIS ACTION IS MADE FINAL even though it is a first action after the filing of a request for continued examination and the submission under 37 C.F.R. § 1.114. See MPEP § 706.07(b). Applicant is reminded of the extension of time policy as set forth in 37 C.F.R. § 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 C.F.R. § 1.17(a)) pursuant to 37 C.F.R. § 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Response to Amendment
This Final Office action is responsive to the request for continued examination filed on February 18, 2026 (hereafter “Response”). The amendments to the claims are acknowledged and have been entered.
Since the amendments to the claims are not patentably distinct (i.e., the new claims could not be restricted from the old), and no new grounds of rejection are raised, this action is made final.
Claims 1, 4, 8, 11, 13, and 15 are now amended.
Claims 1, 3–6, 8, 10–13, 15, 17–19, and 21 are pending in the application.
Response to Arguments
Claim(s) 1, 3, 5, 6, 8, 10, 13, 15, 17, and 19 stand rejected under 35 U.S.C. § 103 as being unpatentable over U.S. Patent Application Publication No. 2024/0289366 A1 (“Hranj”) in view of U.S. Patent Application Publication No. 2005/0138110 A1 (“Redlich”). The Applicant’s traversal of the rejection has been considered in light of the amendments, but is not persuasive.
As the Applicant correctly observes, the rejection indeed equates Hranj’s semantic embeddings with the claimed tags. The Applicant contends that “[s]uch embeddings are intermediate numerical representations,” and that “Hranj does not disclose assigning discrete classification labels to individual document components, nor does Hranj disclose evaluating such labels to determine whether specific components are authorized for inclusion in a generated presentation.” (Response 9). Respectfully, the Examiner does not find this argument persuasive.
Even assuming for the sake of argument that Hranj’s embeddings are merely “intermediate numerical representations,” the Applicant has not explained why these representations cannot be considered “discrete classification labels.” Contrary to the Applicant’s assertion, Hranj’s embeddings are, in fact, assigned to individual document components. See Hranj ¶ 38 (“A semantic embedding is generated for each of the segments of the document”) (emphasis added). And Hranj does evaluate each embedding against the user’s information to determine whether or not to include the embedding’s corresponding content in the summary. Hranj ¶¶ 31–32.
Hranj does not necessarily make this determination with respect to the user’s organizational role, but Redlich is cited to show why it would have been obvious to include such information in both the document tags, the user’s profile, and the determination of which portions to include. The Applicant contends that Redlich “does not disclose identifying document components, assigning classification labels to those components, evaluating tags in combination with a dynamically generated user profile, or assembling a personalized presentation by selectively including only authorized components,” but respectfully, this is a conclusory statement, not an argument. The rejection explained (and current rejection continues to explain) why Redlich does teach all of the foregoing, citing portions of Redlich for each element. The Applicant’s remarks simply fail to engage with the teachings provided from Redlich, so they cannot persuade the Examiner of error.
The Applicant also argues that “[e]ven if Hranj and Redlich were combined, the resulting system would at most summarize content and apply clearance-based filtering,” but “still fail to disclose or suggest classification labels assigned to individual document components and the claimed process of assembling a personalized presentation by evaluating those labels and selectively including only authorized components.” (Response 9–10). The Examiner respectfully disagrees.
Hranj explicitly teaches classification labels assigned to individual document components and the claimed process of assembling a personalized presentation by evaluating those labels and selectively including only relevant components, for all of the reasons given above and in the rejection, and Redlich explicitly teaches why it would have been obvious to limit the selection of relevant components to only authorized components, again, for all of the reasons given in the rejection.
Therefore, all of the claims are rejected, the Applicant’s request for a notice of allowance (Response 10) cannot be granted at this time.
Claim Rejections – 35 U.S.C. § 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 C.F.R. § 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the later invention.
I. Hranj and Redlich teach claims 1, 3, 5, 6, 8, 10, 12, 13, 15, 17, and 19.
Claim(s) 1, 3, 5, 6, 8, 10, 13, 15, 17, and 19 are rejected under 35 U.S.C. § 103 as being unpatentable over U.S. Patent Application Publication No. 2024/0289366 A1 (“Hranj”) in view of U.S. Patent Application Publication No. 2005/0138110 A1 (“Redlich”).
Claim 1
Hranj teaches:
A non-transitory computer-readable medium embodying a program executable in a computing device, the program, when executed by the computing device, being configured to cause the computing device to at least:
As shown in FIG. 1, Hranj teaches a service environment 106 with several program modules—specifically, a signal detector 108, user knowledge base 110, embedding engine 112, personal knowledge system 114, and summarization engine 116. See Hranj ¶¶ 25–26. These program modules (labeled as 420 in FIG. 4) may be stored on a memory 404, so that they are executable by a processing unit 402. See Hranj ¶¶ 49–52 and 55. As will be discussed below, these modules, when executed by the processor, perform most of the functions recited in this claim.
receive, from a user, a request to access a document;
The signal detector 108 is programmed to receive several different types inputs from users requesting access to a document. Hranj ¶ 26. “For instance, a user of user device(s) 102 may execute a search query that generates search results comprising a set of documents,” Hranj ¶ 26, or, the user may interact with “a hyperlink or an icon for a document.” Hranj ¶ 36.
Hranj focuses on what happens when the request involves hovering on the hyperlink or icon, rather than actually clicking it. See Hranj ¶ 36. However, as anyone familiar with the definition of the word “hyperlink” (particular those of ordinary skill in the art) will know, a hyperlink is clickable element that instructs a computer to access the document referenced in the hyperlink.
Consequently, the Examiner finds that this portion of Hranj explicitly teaches receiving a signal from a user hovering on a hyperlink to a document, and further, at least implicitly suggests the user can click on the hyperlink to access the document as well.
identify the user in a user directory;
Next, “signal detector 108 identifies a context of a detected user request for summaries,” which may include “information associated with the user,” Hranj ¶ 27, and provides that context to personal knowledge system 114, which personal knowledge system 114 uses (along with other information) to find data associated with the user in user knowledge base 110. Hranj ¶ 31.
generate a user profile based upon
“User knowledge base 110 aggregates user data from various data sources (e.g., signal detector 108, the user’s application data, data stores external to system 100) and stores the aggregated user data in one or more data structures.” Hranj ¶ 28. As a result of the aggregation, the user knowledge base 110 stores, for each user, “the personalized knowledge graph comprises objects (e.g., documents, document parts, entities) interacted with by the user, relationships between the objects, and metadata associated with the objects and relationships (e.g., creation date, modification date, most recent interaction date, document properties, and entity properties),” as well as “weights or scores that are assigned to the objects based on various factors, such as the date/time the object was added to the personalized knowledge graph, the user’s expertise or familiarity with the object, the user’s interest in the object, the most recent modification of the object, the frequency of the user’s interaction with the object, the total number of user interactions with the object, the user’s most recent interaction with the object, the type of interaction(s) with the object, and so on.” Hranj ¶ 28.
determine, based upon the user profile, whether to provide the user with access to a full version of the document or a redacted version of the document; in response to determining to provide the user with access to the full version of the document, display the full version of the document on a user device associated with the user; and
The system determines whether to provide access to a summarized version of the document, rather than the full version, “in response to a user performing a hovering event on a hyperlink or an icon for a document.” Hranj ¶ 36.
The “full version” branch of the claimed program instructions are italicized above to highlight that Hranj merely suggests a determination to provide access to the full version, rather than explicitly anticipating it. Specifically, as mentioned above, the disclosure of a “hyperlink” to the document at least suggests that the user could click the hyperlink, rather than merely hovering over it.
in response to determining to provide the user with access to the redacted version of the document, identify a plurality of document components of the document;
In order to respond to the summarization request, the system proceeds as follows. First, “[e]mbedding engine 112 separates the document or object into one or more segments using, for example, a data parsing utility.” Hranj ¶ 29.
tag each of the plurality of document components of the document with one or more tags based upon an analysis of content of the document,
Next, “[a] semantic embedding is then generated for each of the segments using an embedding model.” Hranj ¶ 29.
wherein the one or more tags comprise classification labels assigned to individual document components based on the content of the document components;
“In examples, the embedding model factorizes a segment into one or more feature vectors.” Hranj ¶ 29.
generate a personalized presentation of the document based upon the one or more tags of the plurality of document components and the user profile,
After that, “personal knowledge system 114 compares the semantic embeddings to the knowledge information [obtained from user knowledgebase 110],” Hranj ¶ 31, and then decides which “semantic embeddings [] are to be summarized for the user that submitted the user request” based on “evaluation of the comparison.” Hranj ¶ 32.
In any case, personal knowledge engine 114 next provides to summarization engine 116 the “indications of semantic embeddings to be summarized and corresponding summarization instructions (e.g., summarization scope summarization amount, presentation order, output mode),” so that it can generate the actual summary. Hranj ¶ 34.
Recall that claimed tags and user profile respectively correspond to Hranj’s semantic embeddings and knowledge information about the user obtained from the user knowledgebase 110, hence, this summary is indeed based upon the tags of the document components and the user profile.
wherein the personalized presentation is generated by
Paragraphs 31 and 32 discuss how Hranj’s method decide which portions of the content to use for a personalized summary of the content. Both paragraphs will now be discussed in detail below, to show why each of the claimed steps are identical to Hranj’s steps for this process (apart from the use of an “organizational role membership,” which was shown to be obvious in both this rejection and in the previous Office Action for the same reasons).
evaluating, for each document component, the one or more tags associated with the document component in combination with the user profile,
In order to construct a summary, personal knowledge system 114 begins by receiving the semantic embeddings discussed above and knowledge information from the user knowledge base 110, which, like the semantic embeddings of the content, may also be vectorized into its own semantic embeddings. Hranj ¶ 31. Then, “personal knowledge system 114 compares the semantic embeddings to the knowledge information,” e.g., “by calculating a similarity measurement between semantic embeddings and knowledge information, such as a cosine similarity measurement or a Euclidian distance measurement,” which “indicates the similarity in content or topic between a semantic embedding and the knowledge information.” Hranj ¶ 31.
determining, based on the evaluation, whether the document component is authorized for inclusion in the personalized presentation,
Next, “[t]he results of comparing the semantic embeddings to the knowledge information are evaluated based on the context for the user request,” and “[b]ased on evaluation of the comparison, personal knowledge system 114 identifies semantic embeddings that are to be summarized for the user that submitted the user request.” Hranj ¶ 32.
“For example, based on the context for the user request, personal knowledge system 114 may prioritize summarizing semantic embeddings that include new information relating to topics with which the user has expertise or experience, new information relating to topics with which the user has limited knowledge or experience, or known information (e.g., information known by the user) relating to topics with which the user has expertise or extensive experience.” Hranj ¶ 32. As another example, “personal knowledge system 114 may determine that semantic embeddings relating to a particular topic are to be summarized at a high conceptual level (or a low conceptual level), semantic embeddings are to be limited to a particular number of sentences or words, or semantic embeddings are to include supplemental information (e.g., links to additional content).” Hranj ¶ 33.
and assembling the personalized presentation from only those document components determined to be authorized,
“Summarization engine 116 receives indications of semantic embeddings to be summarized and corresponding summarization instructions (e.g., summarization scope summarization amount, presentation order, output mode) from personal knowledge system 114,” and “generates one or more summaries for the semantic embeddings in accordance with the summarization instructions.” Hranj ¶ 34.
such that at least one document component is omitted from the personalized presentation based on the one or more tags and
The summary generation mentioned above omits document components from the presentation, based on both the semantic embeddings (the claimed tags) and at least information about the user (albeit not necessarily his “role”) in at least two different ways.
For one, by “using the similarity measurement between semantic embeddings and knowledge information, such as a cosine similarity measurement or a Euclidian distance measurement,” Hranj ¶ 31, the personal knowledge system 114 is able to decide which semantic embeddings are more responsive to the user’s request than others, and prioritize only the responsive ones over the non-responsive ones. Hranj ¶ 32.
Second, “[p]ersonal knowledge system 114 also determines a summarization scope for each semantic embedding or an amount by which the information associated with each semantic embedding should be summarized, based on the context for the user request.” Hranj ¶ 33. “For example, personal knowledge system 114 may determine that . . . semantic embeddings are to be limited to a particular number of sentences or words
and display the personalized presentation of the document on the user device.
Finally, “[s]ummarization engine 116 provides summaries to user device(s) 102 to fulfill user requests for the summaries,” so that “[t]he summary may then be displayed on or by user device(s) 102 in response to the user request.” Hranj ¶ 34.
In view of the foregoing, Hranj differs from the claimed invention in only two respects: (1) Hranj’s knowledge information about the user is not based upon “an organizational role membership” of the user, and (2) Hranj merely suggests the branch of providing a full version of the document, rather than explicitly anticipating it.
Redlich, however, teaches a “reconstruction routine” (FIGs. 1B, 7a, and 7a(cont.)) that causes a computer to:
receive, from a user, a request to access a document;
“The user, typically at a computer terminal, inputs a reconstruction request 120.” Redlich ¶ 147.
identify the user in a user directory;
“The system first executes a security clearance protocol routine 122 in order to determine whether the user has the proper security clearance,” by searching for an entry associated with the user in “a security code database or list 124.” Redlich ¶ 147.
generate a user profile based upon an organizational role membership of the user within the user directory;
In environments where “multiple users are permitted access to the documents, and those multiple users have different security clearances, the security clearance protocol [also] determines the level of security clearance,” which ultimately causes the security clearance protocol to generate a clearance 126 that includes the user’s security level. Redlich ¶ 147. Specifically, with reference to FIG. 7a and 7a(Cont.) (which illustrate the security clearance protocol with greater detail), the user’s security level corresponds to his membership in a “community of interest” and “the particular security level and security clearance for each community of interest.” Redlich ¶ 205. Notably, much like the Applicant’s specification discloses (but does not yet claim), membership in a “community of interest” (the claimed role) may be hierarchical, per the “Community Security Level Table” printed between paragraphs 205–206 in the Pre-Grant Publication.
determine, based upon the user profile, whether to provide the user with access to a full version of the document or a redacted version of the document;
“Decision 428 determines whether the inquiring party is entitled to full or partial access to the source document.” Redlich ¶ 208.
in response to determining to provide the user with access to the full version of the document, display the full version of the document on a user device associated with the user;
“If YES, the system reconstruct [sic, reconstructs the document] pursuant to the clearance level in step 430,” Redlich ¶ 208, and then displays the reconstructed document in step 432. Redlich ¶ 211.
in response to determining to provide the user with access to the redacted version of the document,
If the answer to decision 428 (full clearance or not) is no, “the NO branch is taken.” Redlich ¶ 208. In the NO branch, the system adds placeholder substitutions for censored document portions, but the details of this process will be discussed together with the relevant claim elements below.
one or more tags comprise classification labels assigned to individual document components based on the content of the document components;
As shown in FIG. 1A, a “map 112” is produced that assigns each of the individual components of a source document 100 to different respective portions of storage, and records that assignment: A-COM 108 is for document components that are not sensitive, while B-Ext 110 is for document components deemed to be of “high security.” Redlich ¶¶ 132 and 134.
The map falls within the scope of the claimed one or more tags, because it describes the security classification assigned to each portion of the document, based on the sensitivity of each portion.
generate a personalized presentation of the document based upon the one or more tags of the plurality of the document components and the user profile,
As shown in FIG. 7a, with or without the placeholders, “the system reconstruct[s] [the document] pursuant to the clearance level in step 430.” Redlich ¶ 208.
Reference is once again made to FIGS. 1a–1b, which illustrate the finer details of document reconstruction. During the reconstruction process (FIG. 1B), the memory map pointing to each respective storage segment of the document (A-com 108 and B-ext 110) is provided, Redlich ¶ 147, and evaluated against the user’s clearance.
wherein the personalized presentation is generated by evaluating, for each document component, the one or more tags associated with the document component in combination with the user profile, determining, based on the evaluation, whether the document component is authorized for inclusion in the personalized presentation,
By applying clearance 126 to the map 128, the system is able to retrieve all of the non-sensitive content segments from A-com 108, and retrieve and decrypt only the appropriate content segments from B-ext 110 falling within the user’s security clearance level. Redlich ¶¶ 147, 171, and 208.
and assembling the personalized presentation from only those document components determined to be authorized, such that at least one document component is omitted from the personalized presentation based on the one or more tags and the organizational role membership of the user
Having retrieved the different portions of the document, the system will then reassemble the document using to comprise only the portions of the document to which the user’s security level provides access. See Redlich ¶¶ 147, 171, and 208.
and display the personalized presentation of the document on the user device.
Returning to FIG. 7a (cont.), after reconstructing the document according to the appropriate clearance level in step 430, “the system displays the plain text in a normal format or utilizing a split or bifurcated video memory or utilizing overlay display screen” in step 432. Redlich ¶ 211.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to enhance Hranj’s user knowledge base 110 with the security information taught by Redlich, thereby allowing the combined system to make decisions about its output based on the user’s security level. One would have been motivated to combine Redlich with Hranj because Redlich’s technique “foster[s] sharing of documentation between different parties, taking into consideration the need to limit the access of other parties to the total content of the owner's document.” Redlich ¶ 218.
Claim 3
Hranj and Redlich teach the non-transitory computer-readable medium of claim 1, wherein the program generates the personalized presentation of the document by causing the computing device to at least:
generate at least one contextual hint corresponding to a first document component from the document; and
“[P]ersonal knowledge system 114 may determine that semantic embeddings relating to a particular topic are to be summarized at a high conceptual level (or a low conceptual level), semantic embeddings are to be limited to a particular number of sentences or words, or semantic embeddings are to include supplemental information (e.g., links to additional content).” Hranj ¶ 33.
cause the at least one contextual hint to be displayed in the personalized presentation alongside the first document component.
“Summarization engine 116 receives indications of semantic embeddings to be summarized and corresponding summarization instructions (e.g., summarization scope summarization amount, presentation order, output mode) from personal knowledge system 114,” and then “generates one or more summaries for the semantic embeddings in accordance with the summarization instructions. For example, a summary may comprise segments that have various summarization scopes and that are arranged in a particular segment presentation order.” Hranj ¶ 34.
Claim 5
Hranj and Redlich teach the non-transitory computer-readable medium of claim 1,
wherein the program generates the user profile based upon a further analysis of a plurality of documents associated with the user in a document archive.
The user knowledge base 110 stores, for each user, “the personalized knowledge graph comprises objects (e.g., documents, document parts, entities) interacted with by the user, relationships between the objects, and metadata associated with the objects and relationships (e.g., creation date, modification date, most recent interaction date, document properties, and entity properties),” as well as “weights or scores that are assigned to the objects based on various factors, such as the date/time the object was added to the personalized knowledge graph, the user's expertise or familiarity with the object, the user's interest in the object, the most recent modification of the object, the frequency of the user's interaction with the object, the total number of user interactions with the object, the user's most recent interaction with the object, the type of interaction(s) with the object, and so on.” Hranj ¶ 28.
Claim 6
Hranj and Redlich teach the computer-readable medium of claim 1,
wherein the one or more tags are generated based upon the analysis of the content of the document by a sequence-to-class deep learning model that takes a sequence of text as an input and returns the one or more tags that represent the sequence of text.
“Embedding engine 112 separates the document or object into one or more segments using, for example, a data parsing utility. A semantic embedding is then generated for each of the segments using an embedding model, such as Bidirectional Encoder Representations of Transformers (BERT), Sentence BERT (SBERT), Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and Word2Vec. In examples, the embedding model factorizes a segment into one or more feature vectors.” Hranj ¶ 29.
Claims 8, 10, 12, and 13
Claims 8, 10, 12, and 13 each recite the same computing device described in the preamble of corresponding claims 1, 3, 5, and 6, which executes exactly the same program instructions. Both the program instructions and the hardware are discussed in the rejection of claims 1, 3, 5, and 6, and therefore, claims 8, 10, 12, and 13 are rejected over the same findings and rationale as provided above for claims 1, 3, 5, and 6.
Claims 15, 17, 19, and 20
Claims 15, 17, and 19 recite exactly the same method that the computing device of claims 8, 10, and 12 performs as part of its normal operation. Therefore, claims 15, 17, and 19 are rejected over the same findings and rationale as provided above for those corresponding claims. See MPEP § 2112.02.
II. Hranj, Redlich, and Rose teach claims 4, 11, 18, and 21.
Claims 4, 11, 18, and 21 are rejected under 35 U.S.C. § 103 as being unpatentable over Hranj and Redlich as applied to claims 1, 8, and 15 above, and further in view of U.S. Patent No. 5,838,323 A (“Rose”).
Claim 4
Hranj and Redlich teach the non-transitory computer-readable medium of claim 1, and strongly suggest the use of a verbosity user interface component by teaching that the signals personal knowledges system 114 uses to determine the verbosity of its summaries may include “user preferences or settings configured for the user, or a stated user objective for a user request,” Hranj ¶ 27, as well as “user signals associated with input data generated by user device(s) 102.” Hranj ¶ 26.
Thus, the only difference between Hranj-Redlich and the claimed invention is that Hranj does not disclose a program that “generates” the verbosity user interface component.
Rose, however, teaches a program that generates the personalized presentation of the document by causing the computing device to at least:
generate a verbosity user interface component facilitating adjustment of the verbosity of the personalized presentation of the document; and
As shown in FIG. 2, a computer program that generates window 201 includes a slider 203 in the window 201, at first set to an “all” setting. Rose col. 4 ll. 52–53.
in response to a change in a selected verbosity level, cause the personalized presentation of the document to be updated.
“Referring now to FIG. 3, the user has moved the slider 203, typically via a cursor control device such as a mouse, trackball, or trackpad, to indicate that he only wants a summary one-eighth the size of the original document (note that predetermined summarization settings, wherein the system automatically generates a preset amount of summarization according to previously set system or user values, are equally supportable with the present invention) to be displayed within the document summary window 201. The summary now fits within the window 201, as indicated by the empty scroll bar 205 on the right hand side of the summary window.” Rose col. 4 l. 64 to col. 5 l. 8.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to supplement Hranj’s input signals with the input signal of adjusting a slider to request a particular level of summarization, as taught by Rose. One would have been motivated to improve Hranj with Rose’s slider because “such interactive control allows the user to expand and contract summarized documents at will, thus freeing the user to focus on the content of the summarized document rather than on trying to determine what amount or percentage is sufficient or how the underlying abstracting mechanism operates.” Rose col. 2 ll. 25–30.
Claim 11
Claim 11 is rejected over the same findings and rationale as provided above for claim 4, taken together with the findings and rationale provided in the earlier rejection of claim 8.
Claim 18
Claim 18 is rejected over the same findings and rationale as provided above for claim 4, taken together with the findings and rationale provided in the earlier rejection of claim 15.
Claim 21
Hranj and Redlich teach the non-transitory computer-readable medium of claim 1, wherein generating the personalized presentation further comprises
regenerating the personalized presentation by re-evaluating the one or more tags associated with the plurality of document components in combination with the user profile to modify which document components are included in the personalized presentation.
Hranj teaches a system that is programmed with instructions for process 200 of FIG. 2, see Hranj ¶¶ 35–36, and process 200 causes Hranj’s system to respond to any (and thus a subsequent) request for document summaries, including requests for document summaries that have different context information depending on the current “user preferences or settings configured for the user, or a stated user objective for a user request,” Hranj ¶ 27, as well as “user signals associated with input data generated by user device(s) 102.” Hranj ¶ 26.
Accordingly, every time the system performs method 200, it performs step 212 of generating a new summary for a document, by first performing steps 204–208, which include “re-evaluating the one or more tags associated with the plurality of document components in combination with the user profile to modify which document com-ponents are included in the personalized presentation” for exactly all of the reasons given in the rejection of claim 1, with respect to “evaluating, for each document component, the one or more tags associated with the document component in combination with the user profile,” “determining, based on the evaluation, whether the document component is authorized for inclusion in the personalized presentation.”
That is, just as Hranj performed those steps a first time for a first context that specified a first level of verbosity, Hranj necessarily performs these steps once again when it receives a subsequent summarization request with new context specifying a new level of verbosity.
Thus, the only difference between Hranj-Redlich and the claimed invention is that Hranj does describe the nature of the claimed “verbosity user interface component.”
Rose, however, teaches a program that generates the personalized presentation of the document by causing the computing device to at least:
generating a verbosity user interface component configured to receive a user-selected verbosity level, and,
As shown in FIG. 2, a computer program that generates window 201 includes a slider 203 in the window 201, at first set to an “all” setting. Rose col. 4 ll. 52–53.
in response to a change in the user-selected verbosity level, regenerating the personalized presentation
“Referring now to FIG. 3, the user has moved the slider 203, typically via a cursor control device such as a mouse, trackball, or trackpad, to indicate that he only wants a summary one-eighth the size of the original document (note that predetermined summarization settings, wherein the system automatically generates a preset amount of summarization according to previously set system or user values, are equally supportable with the present invention) to be displayed within the document summary window 201. The summary now fits within the window 201, as indicated by the empty scroll bar 205 on the right hand side of the summary window.” Rose col. 4 l. 64 to col. 5 l. 8.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to supplement Hranj’s input signals with the input signal of adjusting a slider to request a particular level of summarization, as taught by Rose. One would have been motivated to improve Hranj with Rose’s slider because “such interactive control allows the user to expand and contract summarized documents at will, thus freeing the user to focus on the content of the summarized document rather than on trying to determine what amount or percentage is sufficient or how the underlying abstracting mechanism operates.” Rose col. 2 ll. 25–30.
Conclusion
All claims are identical to or patentably indistinct from, or have unity of invention with claims in the application prior to the entry of the submission under 37 C.F.R. § 1.114 (that is, restriction (including a lack of unity of invention) would not be proper) and all claims could have been finally rejected on the grounds and art of record in the next Office action if they had been entered in the application prior to entry under 37 C.F.R. § 1.114. Accordingly, THIS ACTION IS MADE FINAL even though it is a first action after the filing of a request for continued examination and the submission under 37 C.F.R. § 1.114. See MPEP § 706.07(b). Applicant is reminded of the extension of time policy as set forth in 37 C.F.R. § 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 C.F.R. § 1.17(a)) pursuant to 37 C.F.R. § 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Justin R. Blaufeld whose telephone number is (571)272-4372. The examiner can normally be reached M-F 9:00am - 4:00pm ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James K Trujillo can be reached at (571) 272-3677. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Justin R. Blaufeld
Primary Examiner
Art Unit 2151
/Justin R. Blaufeld/Primary Examiner, Art Unit 2151
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