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 .
Response to Amendment
The Office Action is responsive to amendments filed for application 18/712,717 filed on 07/06/2026.
Please note claims 1-20 remain in the application.
In response to the amendments filed to the title of the invention, the objection to the title of the invention has been withdrawn.
In response to the amendments filed to claims 1, 4, and 8, the previous rejection(s) under 35 U.S.C 112(b) of claims 1-20 has been withdrawn.
In response to the amendment filed to claim 20, the previous rejection(s) under 35 U.S.C 101 of claims 20 has been withdrawn.
Response to Arguments
Applicant’s arguments, see pg. 11, line 4, filed 07/06/2026, with respect to the drawing objections have been fully considered and are persuasive. The objections to figures 1, 13, and 19 have been withdrawn.
Applicant's arguments filed 07/06/2026, pg. 12, line 12, regarding the rejection of claim 1 under 35 U.S.C. 102(a)(1) have been fully considered but they are not persuasive.
Regarding claim 1, applicant argues that Tiwari does not disclose “wherein the extracted section satisfying the predetermined condition as the feature trend is displayed according to whether a difference between the distribution of features in the current period and the distribution of features in the prediction period satisfies a difference threshold.”
Tiwari discloses wherein the predetermined condition to be satisfied is whether a distribution of features in the current period and the distribution of features in the prediction period satisfy a difference threshold. See Tiwari ¶[0051], copied below with added emphasis and footnotes.
[0051] At block 432, process 400 can sort the n-grams within each region and/or vertical category based on the corresponding prediction values computed at block 430. At block 434, process 400 can identify the n-grams with predicted change values* above a threshold. In various implementations, these can be the n-grams with a predicted change value above an overall threshold or above a threshold for the particular region and/or vertical category. For example, process 400 can select the top five n-grams in each category. In some implementations, only n-grams with above a threshold predicted change value are selected**. For example, process 400 can select the top five n-grams in each category, as long as each selected n-gram has a predicted change score of at least +0.5. Process 400 then continues to block 436, where it ends.
*The change value being a change between a current period and a prediction period per Tiwari ¶[0050].
**N-grams are selected for display, per Tiwari ¶[0016], ¶[0059], explained in detail in the rejection of claim 9 contained within the non-final rejection dated 04/03/2026.
As the predetermined condition for identifying a feature trend is whether or not the difference between current and predicted distributions of features satisfy a threshold, and as these feature trends are displayed, Tiwari does in fact disclose wherein the extracted section satisfying the predetermined condition as the feature trend is displayed according to whether a difference between the distribution of features in the current period and the distribution of features in the prediction period satisfies a difference threshold.
It is additionally noted by the examiner that claim 2, currently rejected under 35 U.S.C. 103 over Tiwari in view of McGilliard, recites wherein the predetermined condition is met when “a value is lower than a threshold in the distribution in the current period and the value is higher than the threshold in the distribution in the prediction period.” The difference between the lower “current period” threshold value and higher “prediction period” threshold value constitutes a difference threshold between the distribution of features in the current period and the distribution of features in the prediction period. Therefore McGilliard, as relied upon in the rejection of claim 2, would cure any deficiencies present in Tiwari.
Regarding claim 19 and 20, Applicant argues that these claims are distinguished over Tiwari for similar reasons as claim 1. However, claims 19 and 20 have not been amended to include the additional limitations of amended claim 1, which form the basis of applicant’s arguments.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 9, 13-15, and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tiwari, US-PG-PUB 2019/0102374 (previously cited).
Regarding claim 1, Tiwari discloses an information processing apparatus (The methods disclosed are implemented via computers (information processing apparatus).....¶[0019], lines 1-3) comprising; circuitry (Computers comprise circuitry) configured to
acquire a distribution of features (Groups of social media posts are processed to acquire a set of “n-grams” (keyword-based features) which are classified as part of a dataset (thus providing a distribution).....¶[0044], lines 1-3, ¶[0045], lines 1-2, ¶[0048], lines 1-3) of a target content (Content items, (e.g. social media posts).....¶[0040], lines 5-6) in at least one predetermined period (Particular time period.....¶[0040], lines 5-7),
acquire a distribution of features (After processing the original set of posts, a prediction of how much each “n-gram” will be trending (i.e.: how they’ll be distributed in future social media posts.....¶[0050], lines 1-3) in a prediction period (Prediction of a future period.....¶[0050], lines 2-3) based on the distribution of the features aggregated for each predetermined period (The predictions are made on the basis of the occurrence (trending, distribution) of n-grams from the particular past time period.....¶[0050], lines 4-6), and
compare a distribution of features in a current period with the distribution of the features in the prediction period (The change values of n-gram features over time are evaluated, comparing the distribution of each feature at the time the dataset was generated (the current period) to the distribution of each future in the future (the prediction period).....¶[0051], lines 4-8) to extract a section satisfying a predetermined condition (Change values above a threshold (predetermined condition) are identified (extracted).....¶[0051], lines 4-5) as a feature trend in the prediction period (The data is used to anticipate (predict) n-grams (features) that trend in the future (prediction period).....¶[0052], lines 2-4), wherein the extracted section satisfying the predetermined condition as the feature trend is displayed (Shown in Fig. 6B, graphs (653) indicating the numerical values of extracted feature trends are included in displayed reports.....¶[0059], lines 12-15) according to whether a difference between the distribution of features in the current period and the distribution of features in the prediction period satisfies a difference threshold (Feature trends may only be selected and displayed if they satisfy a threshold predicted change value between a current and prediction period (difference threshold).....¶[0051], lines 5-12).
Regarding claim 9, Tiwari discloses the information processing apparatus according to claim 1, wherein the circuitry is further configured to perform control to display a screen (The CPU communicates with a display controller.....¶[0016], lines 5-7) indicating the feature trend (Predicted feature trends are indicated to the user via topic reports.....¶[0059], lines 1-3) in the prediction period on a display (A display unit provides graphical feedback to a user.....¶[0016], lines 7-9).
Regarding claim 13, Tiwari discloses the information processing apparatus according to claim 9, wherein the screen includes a display indicating a numerical value of a section extracted as the feature trend (Shown in Fig. 6B, graphs (653) indicating the numerical values of extracted feature trends are included in displayed reports.....¶[0059], lines 12-15).
Regarding claim 14, Tiwari discloses the information processing apparatus according to claim 9, wherein the circuitry is further configured to acquire a distribution of features in the prediction period for each feature of the target content (Predictions of distributions are made for each feature selected via processing target content…..¶[0050], lines 1-3), calculate, for each feature, a distance between a distribution of features in the current period and a distribution of features in the prediction period (For each selected feature, a change value is calculated, reflective of the amount of change (distance) of distribution of features from the current period to the prediction period.....¶[0051], lines 3-5), and extract the feature trend for each feature after excluding features whose distance is less than a threshold (Feature trends are identified (extracted) for features where the amount of change is above an identified threshold.....¶[0051], lines 3-5).
Regarding claim 15, Tiwari discloses the information processing apparatus according to claim 14, wherein the screen displays each feature trend (Shown in Fig. 6B, reports for growing conversations (predicted feature trends) are listed in order of most likely to trend per the process identified in the rejection of claims 1, 9, and 14.....¶[0060], lines 1-3) in descending order of the distance (The metric used for prediction, calculated by the method of Tiwari is chxange value, previously identified as a distance. This can also be seen in Fig. 5, where pairs of trending topics are ordered in descending order by values (502, 504, 506, 508).....¶[0051], lines 3-8).
Regarding claim 18, Tiwari discloses the information processing apparatus according to claim 1, wherein the circuitry is further configured to perform control to extract the feature trend on based on a distribution obtained by combining a plurality of features (n-gram features may be sorted according to regions, a separate feature category, comprising a plurality.....¶[0041], lines 5-7, ¶[0051], lines 1-2) and perform control to display the extracted feature trend on a multi-dimensional grid (Shown in Fig. 6B, “Growing Conversations” (predicted feature trends) may be displayed as part of a report, with the trends themselves plotted as line charts on a cartesian plane (a type of multi-dimensional grid).....¶[0060], lines 1-3 )
Claim 19 is rejected under the disclosure of Tiwari as in claim 1 above.
Regarding claim 20, the method steps recited are present in claim 1, and disclosed by Tiwari as taught in the rejection in claim 1 above.
Tiwari additionally discloses a non-transitory computer-readable storage medium having embodied thereon a program, which when executed by a computer causes the computer to execute the method (¶[0018], full text).
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.
Claims 2, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Tiwari in view of McGilliard, US Patent No. 9,753,988 (previously cited).
Regarding claim 2, Tiwani discloses, as explained above, the information processing apparatus according to claim 1, but fails to explicitly disclose wherein the section satisfying the predetermined condition includes a section in which a value is lower than a threshold in the distribution in the current period and the value is higher than the threshold in the distribution in the prediction period.
McGilliard teaches an information processing method for predicting trending artists (analogous to the trending n-gram features of Tiwani), wherein a section (of artists) satisfying the predetermined condition is a section in which a value is lower than a threshold in the distribution in the current period (Artists that are already (in a current period) popular (not below a popularity threshold) are filtered out (as they do not satisfy the predetermined condition)…..Col. 9, line 66-67) and the value is higher than the threshold in the distribution in the prediction period (Artists that are determined to become popular (rise above the popularity threshold) in the future (prediction period) are selected as the section for display…..Col. 10, lines 39-41).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tiwani by McGilliard to provide the benefit of avoiding mistaking already popular topics as potentially becoming popular (McGilliard, Col. 9, lines 1-2). Such modification would make obvious the feature(s) wherein the section satisfying the predetermined condition includes a section in which a value is lower than a threshold in the distribution in the current period and the value is higher than the threshold in the distribution in the prediction period.
Regarding claim 16, Tiwani discloses the information processing apparatus according to claim 1, but fails to explicitly disclose wherein the circuitry is further configured to extract an artist associated with music in which at least one of the extracted feature trends matches, instead disclosing extracting general pop culture trends such as trending television shows (Seen in Fig. 6B, Scooby Doo is identified as an extracted feature trend).
McGilliard teaches a method of predicting a number of listeners (a feature) of target content in a future period based on analysis of current listeners in a current period (Generally explained in Col. 2, lines 23-30), analogous to the method of Tiwani, wherein a control unit (Methods are implemented by a processor (control unit)…..Col. 12, lines 17-21) extracts an artist associated with music (The method identifies (extracts) artists and songs predicted to become popular…..Col. 7, lines 15-18) in which at least one of the extracted feature trends matches (The identification is based on listener (feature) trends.....Col 7, lines 18-21).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tiwani by McGilliard to provide the benefit of business methods for media providers that promote obscure artists that may become popular, earning revue for said providers and artists (McGilliard, Col 3, lines 24-33). Such modification would make obvious the feature(s) wherein the circuitry is further configured to extract an artist associated with music in which at least one of the extracted feature trends matches
Regarding claim 17, the combination of Tiwani and McGilliard, as explained above, teach the information processing apparatus according to claim 16.
Tiwani additionally teaches wherein the the circuitry is further configured to perform control to display the extracted feature trend (Predicted feature trends are displayed to a user via topic reports.....¶[0059], lines 1-3), as well as the extracted topic, but fails to teach wherein the control unit performs control to display extracted artists and music.
McGilliard additionally teaches displaying extracted artists and music (Shown in Fig. 4, a user interface displays artists and songs predicted to become popular at symbol (414)…..Col. 11, lines 48-51).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Tiwani and McGilliard further by McGilliard to provide the benefit of business methods for media providers that promote obscure artists that may become popular, earning revue for said providers and artists (McGilliard, Col 3, lines 24-33). Such modification would make obvious the feature(s) wherein the circuitry is further configured to perform control to display extracted artists and music.
Claims 3-8, and 10, are rejected under 35 U.S.C. 103 as being unpatentable over Tiwari in view of “Music Popularity: Metrics, Characteristics, and Audio-based Prediction” [online]. IEEE Transactions on Multimedia, 2018 (hereinafter Lee) (previously cited).
Regarding claim 3, Tiwani discloses, as explained above, the information processing apparatus according to claim 1, but fails to disclose wherein the target content includes content that satisfies a condition indicating popularity.
Lee teaches a method of predicting trending popular music features based on evaluating target content, wherein the target content (Content used for training prediction models…..Pg. 7, Heading D, 1, lines 6-8) is content that satisfies a condition indicating popularity (Songs are chosen based on the Billboard Hot 100 chart, which ranks music based on popularity.....Pg. 7, heading D, 1, lines 6-10).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tiwani by Lee to provide the benefit of predicting popularity of future content based on analysis of multiple aspects of popularity over time (Lee, Pg. 2, Col. 1, subheading “1)”, lines 3-8). Such modification would make obvious the feature(s) wherein the target content includes content that satisfies a condition indicating popularity.
Regarding claim 4, the combination of Tiwani and Lee, as explained above, teach the information processing apparatus according to claim 3.
Lee additionally teaches wherein whether the target content includes content that satisfies a condition indicating popularity as the target content is determined based on data acquired from a designated data sharing platform (Songs are chosen based on the Billboard Hot 100 chart, a platform which provides (shares) data about popularity of music.....Pg. 3, Col. 2, section III, subsection A, lines 1-7).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Tiwani and Lee by Lee to provide the benefit of predicting popularity of future content based on analysis of multiple aspects of popularity over time (Lee, Pg. 2, Col. 1, subheading “1)”, lines 3-8). Such modification would make obvious the feature(s) wherein the target content includes content that satisfies the condition indicating the popularity as the target content is determined based on data acquired from a designated data sharing platform.
Regarding claim 5, the combination of Tiwani and Lee, as explained above, teach the information processing apparatus according to claim 4.
Lee additionally teaches wherein the content includes music (Billboard Hot 100 is a music popularity service.....Pg. 3, Col. 2, section III, subsection A, lines 1-2), and wherein the condition indicating the popularity includes a number of times of reproduction in the data sharing platform (Popularity ranking is based on amount (number of times) of radio airplay and streaming activity, modes of music reproduction…..Pg. 3, Col. 2, section III, subsection A, lines 5-7).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Tiwani and Lee by Lee to provide the benefit of predicting popularity of future content based on analysis of multiple aspects of popularity over time (Lee, Pg. 2, Col. 1, subheading “1)”, lines 3-8). Such modification would make obvious the feature(s) wherein the content includes music, and the condition indicating the popularity includes a number of times of reproduction in the data sharing platform.
Regarding claim 6, the combination of Tiwani and Lee, as explained above, teach the information processing apparatus according to claim 5.
Lee additionally teaches wherein features of the distribution include a rhythm of music (Shown on pg. 8 in Fig. 7 and described immediately below the figure, predictions of popularity (Y) are made based on various features (X), including rhythm complexity features).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Tiwani and Lee by Lee to provide the benefit of predicting mean popularity content over time (Lee, Pg. 7, Col. 2, section E-1, lines 20-23). Such modification would make obvious the feature(s) wherein the features of the distribution include a rhythm of music.
Regarding claim 7, Tiwani discloses the information processing apparatus according to claim 1, wherein the circuitry uses the distribution of the features in a plurality of predetermined periods as input data (The predictions may be made on the basis of the occurrence (trending, distribution) of n-grams from the past time periods comprising a plurality of months, thus using them as input data.....¶[0050], lines 4-6), but fails to disclose acquiring the distribution of the features in the prediction period by prediction using the input data input into a learned model, instead teaching wherein the model is derived on the basis of polynomial curves (¶[0012], lines 5-9).
Lee teaches a method of predicting trending popular music features based on evaluating target content, which operates by acquiring a distribution of the features in a prediction period (Features determined from training data (reflective of a current period between 6/13/2009 and 11/11/2012) are used to determine the popularity distribution of those same features in a prediction period from 11/11/2012 to 4/19/2014…..Pg. 7, Col 1, Section D-1, lines 6-12, and section D-2, lines 10-12) by prediction using the input data (The training data) into a learned model (The research of Lee considers using different approaches to form popularity predictions, including the use of SVM, and CNN, machine learning (learned model) algorithms…..Pg. 9, Col 2, “Appendix”, lines 1-5, 13-15).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tiwani by Lee to provide the benefit of prediction accuracy with less training data (Lee, Pg. 9, Col 2, “Appendix”, lines 14-20). Such modification would make obvious the feature(s) of acquiring the distribution of the features in the prediction using the input data input into a learned model.
Regarding claim 8, the combination of Tiwani and Lee, as explained above, teach the information processing apparatus according to claim 7.
Lee additionally teaches wherein the circuitry is further configured to generate the learned model used for the prediction by using prescribed machine learning (The learned model uses support vector machines (SVMs) (a prescribed machine learning model)…..Pg. 7, Col 2, section D-2, lines 1-5) with data regarding the target content satisfying a condition indicating popularity, acquired from a designated data sharing platform, as learning data (The SVMs are trained on (and learn from) content (data) chosen based on the Billboard Hot 100 chart, which ranks music based on popularity.....Pg. 7, Col 2, section D-1, lines 6-10).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Tiwani and Lee by Lee to provide the benefit of predicting mean popularity of content over time (Lee, Pg. 7, Col. 2, section E-1, lines 20-23). Such modification would make obvious the feature(s) wherein the circuitry is further configured to generate the learned model used for the prediction by using prescribed machine learning with data regarding the target content satisfying a condition indicating the popularity, acquired from a designated data sharing platform, as learning data.
Regarding claim 10, Tiwani, as explained above, discloses the information processing apparatus according to claim 9, but fails to disclose wherein the screen includes the section extracted as the feature trend is highlighted on a one-dimensional grid.
Lee teaches a method of predicting trending popular music features based on evaluating target content, wherein results are displayed on a screen in which the section extracted as the feature trend (Shown in Fig. 7, popularity predictions for different audio characteristics (feature trends) on the X axis are plotted against different metrics for popularity on the Y axis…..Pg. 7, Col. 2, section E-1, lines 1-3) is highlighted (Each feature trend is assigned a color based on strength, highlighting stronger trends over weaker ones) on a one-dimensional grid (Each row evaluating results for feature vs popularity forms its own 1x20 (one-dimensional) grid.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Tiwani by Lee to provide appropriate matching of audio features to the desired metric for popularity (Discussed in detail in Lee, Pg. 7, Col. 2, heading E (Results)). Such modification would make obvious the feature(s) wherein the screen includes the section extracted as the feature trend is highlighted on a one-dimensional grid.
Allowable Subject Matter
Claims 11 and 12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: Search was conducted in the field of business methods and data processing/analysis, with a focus on music-focused data processing. While search yielded prior art teaching the material of the independent claims, and several dependent claims through the combination of art cited in the rejections above (Tiwani, Lee, McGilliard), none of these, or other prior art located teach the limitations of claim 11, wherein the screen is a screen in which a section having a value higher than a threshold in the current period and a section having a value higher than the threshold in the prediction period are indicated on a one-dimensional grid, and further a section extracted as the feature trend among sections having a value higher than the threshold in the prediction period is emphasized.
The examiner notes that support for specific terms of this claim are taken from applicant’s figures 13 and 14 and corresponding sections of the written description, and that the one-dimensional grid is understood by the examiner to indicate the row of two-dimensional cells at the bottom of fig. 13, which is one-dimensional in the sense that it is a single row of cells, while the cells themselves have two dimensions such that the data from the current and prediction periods may be combined into one figure (e.g. using shading or hashing) displayed as a part of a screen of a user interface as indicated in fig. 14. Additionally, the emphasized sections are understood to be the sections of Figs. 13 and 14 where a bolded border is drawn around a section on the one-dimensional grid.
Additional search was conducted in the fields of information graphics and business methods to find prior art that teaches this method of displaying information. The closest prior art located is Grounds et al, US-PG-PUB No. 2015/0052485 (previously cited), which teaches using a single column to summarize reported data for machine maintenance alerts, but this fails to meet all the limitations as stated above, at least because the reported data is for live status updates of machinery, which is not considered by the examiner to be sufficiently analogous to predicted status trends to make the claimed material obvious.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lewis, US Patent No. 9,213,949 teaches a system for performing data analysis and establishing and predicting future trending music in a given location.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN RINEHART whose telephone number is (571)272-2778. The examiner can normally be reached M-F 10:00 AM - 6:00 PM 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, Ahmad Matar can be reached on (571) 272-7488. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SEAN RINEHART/Examiner, Art Unit 2694
/ALEXANDER KRZYSTAN/Primary Examiner, Art Unit 2694
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