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 .
Introduction
The following is a non-final Office Action in response to Applicant’s submission filed on June 17, 2025.
Currently claims 1-30 are pending. Claim 1 is independent.
Continuation
This application is a continuation application of U.S. application no. 17/448,740 filed on 09/24/2021 (“Parent Application”), and a U.S. provisional application no. 63/082,865 filed on 09/24/2020. See MPEP §201.07. In accordance with MPEP §609.02 A. 2 and MPEP §2001.06(b) (last paragraph), the Examiner has reviewed and considered the prior art cited in the Parent Application. Also in accordance with MPEP §2001.06(b) (last paragraph), all documents cited or considered ‘of record’ in the Parent Application are now considered cited or ‘of record’ in this application. Additionally, Applicant(s) are reminded that a listing of the information cited or ‘of record’ in the Parent Application need not be resubmitted in this application unless Applicants desire the information to be printed on a patent issuing from this application. See MPEP §609.02 A. 2. Finally, Applicants are reminded that the prosecution history of the Parent Application is relevant in this application. See e.g., Microsoft Corp. v. Multi-Tech Sys., Inc., 357 F.3d 1340, 1350, 69 USPQ2d 1815, 1823 (Fed. Cir. 2004) (holding that statements made in prosecution of one patent are relevant to the scope of all sibling patents).
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/17/2025 appears to be in compliance with the previsions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner.
Claim Rejection – 35 U.S.C. § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 26 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Regarding claim 26, the phrase “such as” renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). Applicants are required to particularly point out and distinctly claim the subject matter which applicants regards as the invention.
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.
Claims 1-30 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As per Step 1 of the subject matter eligibility analysis, it is to determine whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
In this case, claims 1-30 are directed to a method for predicting a future event for a user without tied to a particular machine for performing the steps, which falls outside of the four statutory categories. However, claims 1-30 will be included in Step 2 Analysis for the purpose of compact prosecution.
With respect to claims 1-30, the claims are directed to non-statutory subject matter because the claims are directed to a method without tied to a particular machine in the body of the claims for performing the steps. One factor to consider when determining whether a claim recites a §101 patent eligible process is to determine if the claimed process (1) is tied to a particular machine or; (2) transforms a particular article to a different state or thing. See In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008) (en banc) aff’d, Bilski v. Kappos, 561 U.S. ___, 130 S.Ct. 3218, 95 USPQ2d 1001 (U.S. 2010). (Machine-or-Transformation Test).
In Step 2A of the subject matter eligibility analysis, it is to “determine whether the claim at issue is directed to a judicial exception (i.e., an abstract idea, a law of nature, or a natural phenomenon). Under this step, a two-prong inquiry will be performed to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance), then determine if the claim recites additional elements that integrate the exception into a practical application of the exception. See 2019 Revised Patent Subject Matter Eligibility Guidance (2019 Guidance), 84 Fed. Reg. 50, 54-55 (January 7, 2019).
In Prong One, it is to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance, a law of nature, or a natural phenomenon).
The claims recite limitations of “receiving sequence of free-living activity data, filtering and normalizing the sequence of free-living activity data, transforming the filtered activity data into a sequence of multidimensional vectors through feature extraction, processing the sequence of multidimensional vectors with a trained machine learning model, mapping the output multidimensional vector into a next experience for the user, generating a suggestion for the user, and delivering the suggestion to the user, training a machine learning model using a first set of labeled sequential even data, identifying patterns in the sequence of multidimensional vectors by analyzing temporal relationships, determining a confidence score for the next experience event, comparing the sequence of free-living activity data to activity data of users in similar location, age group, or demographics, identifying temporal relationships, calculating a similarity score, detecting anomalies in the sequence of free-living activity data”. None of the limitations recites technological implementation details for any of these steps, but instead recite only results desired by any and all possible means. The limitations, as drafted, are directed to processes, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “captured with one or more electronic devices”, nothing in the claim elements precludes the steps from practically being performed in the mind (including an observation, evaluation, judgment, opinion), or by a human using a pen and paper. For example, the claim encompasses a person can manually receiving the user activity data, manipulating the data, and providing a suggestion to the user. The recited “one more electronic devices” for capturing activity data is directed to the use of insignificant extract-solution activity of data gathering. Further, using a “trained machine learning model” is merely adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement the abstract idea on a computer. The Supreme Court has repeatedly made clear that merely limiting the field of use of the abstract idea to a particular existing technological environment does not render the claims any less abstract. See Affinity Labs of Texas, LLC v. DirecTV, LLC, 838 F.3d 1253, 1258 (Fed. Cir. 2016). As to learning/training per se, such an argument overlooks the entire education system. Reciting machine learning is placing such learning in a computer context, offering no technological implementation details beyond the conceptual idea to use a machine for learning. Thus, the claims fall within the mental processes grouping. See Under the 2019 Guidance, 84 Fed. Reg. 52. Accordingly, the claims recite an abstract idea, and the analysis is proceeding to Prong Two.
In Prong Two, it is to determine if the claim recites additional elements that integrate the exception into a practical application of the exception.
Beyond the abstract idea, the claims recite the additional elements of “one or more electronic devices” and “a trained machine learning model”. The Specification describes the “User behavior may be ingested/collected via one or more electronic devices that capture data related to a user’s activities and/or behavior over a period of time. Data may include location data, audio data, video data, image data, social profile, search queries, purchase history/habit, movement, the physical state and/or physiological data of an individual (heart rate, temperature), and the like” (see ¶ 42). Thus, the additional elements are recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating, and transmitting information over a network. In addition, reciting “one or more electronic devices” for capturing activity data is directed to the use of insignificant extra solution activity for data gathering. See OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). However, simply using one or more electronic devices tor capturing the user activity data do not integrate the abstract idea into a practical application because nothing in the claims that reflects an improvement to the functioning of a computer itself or another technology. Therefore, the claims are directed to an abstract idea, the analysis is proceeding to Step 2B.
In Step 2B of Alice, it is "a search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept’ itself.’” Id. (alternation in original) (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1294 (2012)).
The claims as described in Prong Two above, nothing in the claims that integrates the abstract idea into a practical application. The same analysis applies here in Step 2B.
Beyond the abstract idea, the claims recite the additional elements of “one or more electronic devices”. The Specification describes the “User behavior may be ingested/collected via one or more electronic devices that capture data related to a user’s activities and/or behavior over a period of time. Data may include location data, audio data, video data, image data, social profile, search queries, purchase history/habit, movement, the physical state and/or physiological data of an individual (heart rate, temperature), and the like” (see ¶ 42). Thus, the additional elements are recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating, and transmitting information over a network. The one or more electronic devices, at best, may perform the generic computer functions including receiving the captured activity data, and delivering (transmitting) the suggestion over a network to the user. However, generic computer components for performing generic computer functions have been recognized by the courts as merely well-understood, routine, and conventional functions of generic computers. See MPEP 2106.05 (d) (II) (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)). Thus, simply implementing the abstract idea on a generic computer for performing generic computer functions do not amount to significantly more than the abstract idea. (MPEP 2106.05(a)-(c), (e-f) & (h)).
For the foregoing reasons, claims 1-30 cover subject matter that is judicially-excepted from patent eligibility under § 101 as discussed above. Therefore, the claims as a whole, viewed individually and as a combination, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-30 are rejected under 35 U.S.C. 103 as being unpatentable over Duffy (US 2020/0081906), and in view of Miller et al., (US 2018/0268337, hereinafter: Miller), and further in view of Feldman et al., (US 2008/0320078, hereinafter: Feldman).
Regarding claim 1, Duffy discloses a computer-implemented method for predicting a future event for a user (see ¶ 45), the method comprising:
preprocessing the sequence of free-living activity data by filtering and normalizing the sequence of free-living activity data to generate filtered activity data (see ¶ 35, ¶ 49, ¶ 82, ¶ 112, ¶ 188, ¶ 371);
transforming the filtered activity data into a sequence of multidimensional vectors through feature extraction, wherein each multidimensional vector comprises computed values for one or more personal, professional, or cultural components of a corresponding free-living activity (see ¶ 50, ¶ 63-64, ¶ 70-72, ¶ 149, claim 4);
processing the sequence of multidimensional vectors with a trained machine learning model that has been trained to recognize temporal patterns in sequences of user activities, wherein the machine learning model generates an output multidimensional vector based on the sequence of multidimensional vectors (see ¶ 47-50, ¶ 96-102, ¶ 121);
mapping, the output multidimensional vector into a next experience for the user (see ¶ 46-47, ¶ 50, ¶ 128, ¶ 149).
Duffy discloses a system comprises a user interaction module that receives queries and query refinement input form a user (see ¶ 26); and the system incorporates the user’s input to create a refined query includes information regarding the initial query and information derived from the iterative sequence of refinements made by the user (see ¶ 112).
Duffy does not explicitly disclose the following limitations; however, Miller in an analogous art for managing user activity data discloses
receiving sequences of free-living activity data of the user captured with one or more electronic devices (see Abstract; Fig. 5, # 508; ¶ 82, ¶ 85, ¶ 158, ¶ 160).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy to include the teaching of Miller in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more specific type of data. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Miller discloses presenting the content comprises one or more suggestions, recommendations, or relevant information based on one or more tasks in the task list of an objective for enhancing computer-human interaction (see ¶ 146).
Duffy and Miller do not explicitly disclose the following limitations; however, Feldman in an analogous art for providing event recommendations discloses
generating a suggestion for the user based on the next experience, wherein the suggestion is designed to enhance at least one of the personal, professional, or cultural components of the next experience (see ¶ 13-14, ¶ 18, ¶ 32, claim 15); and
delivering the suggestion to the user (see ¶ 13, ¶ 17, ¶ 24-25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
In addition, the phrase(s) “wherein each multidimensional vector comprises computed values for one or more personal, professional, or cultural components” merely characterizing the multidimensional vector is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Further, phrase(s) “designed to enhance at least one of the personal, professional, or cultural components of the next experience” is not given patentable weight when it simply expresses the intended result of a process step positively recited. See Minton v. Nat’l Ass’n of Securities Dealers, Inc., 336 F.3d 1373, 1381, 67 USPQ2d 1614, 1620 (Fed. Cir. 2003). If Applicant desires to given the functional phrase(s) a greater patentable weight, the Examiner respectfully recommends Applicant to positive recite the function in the claim.
Regarding claim 2, Duffy discloses the method of claim 1, further comprising training a machine learning model using a first set of labeled sequential event data to create a mapping between sequences of events and corresponding subsequent events, wherein each event is characterized by one or more values for personal, professional, or cultural components (see ¶ 47, ¶ 70, ¶ 112, ¶ 124).
Regarding claim 3, Duffy discloses the method of claim 2, wherein the training comprises training on data of the user (see ¶ 118, ¶ 123, ¶ 286).
Regarding claim 4, Duffy discloses the method of claim 2, wherein the training comprises training on data of users who achieved success (see ¶ 35, ¶ 47, ¶ 50, ¶ 120, ¶ 123).
Regarding claim 5, Duffy discloses training a machine learning in various techniques including deep learning, neural networks (see ¶ 50).
Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 2, wherein the training comprises at least one of supervised or unsupervised training (see ¶ 123). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 6, Duffy discloses retrain or update the models based on the most recent set of feedback (see ¶ 123).
Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 2, wherein the trained machine learning model is periodically retrained using newly collected sequential free-living activity data (see ¶ 82, ¶ 94). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 7, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, further comprising identifying patterns in the sequence of multidimensional vectors by analyzing temporal relationships and transitions between successive vectors in the sequence (see ¶ 15, ¶ 59, ¶ 63, ¶ 94). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 8, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 7, further comprising determining a confidence score for the next experience event based on similarity between the identified patterns and patterns in the training data (see ¶ 15, ¶ 79, ¶ 93-94, ¶ 109-110). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 9, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the next experience is at least one of an activity, a career path, an educational milestone, or a travel destination (see ¶ 128, ¶ 144). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
In addition, claim 9 merely describes the type of next experience is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 10, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein preprocessing further comprises filtering the sequence of free-living activity data to remove data using a filtering algorithm configured to identify patterns associated with user-specific activities (see ¶ 15, ¶ 123, ¶ 148). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 11, Duffy discloses the method of claim 10, wherein the filtering further comprises comparing the sequence of free-living activity data to activity data of users in similar locations, age groups, or demographics to identify activities and data that are likely representative of customary or routine behaviors (see ¶ 45, ¶ 70, ¶ 149-150, ¶ 163, ¶ 168).
Regarding claim 12, Duffy discloses the method of claim 1, wherein feature extraction further comprises identifying temporal relationships between successive free-living activities to compute values for the personal, professional, and cultural components (see ¶ 54, ¶ 58).
Regarding claim 13, Duffy discloses the method of claim 1, wherein the trained machine learning model is a neural network trained to recognize temporal patterns in sequence of user activities (see ¶ 140, ¶ 241).
Regarding claim 14, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein mapping further comprises calculating a similarity score between the output multidimensional vector and historical multidimensional vectors (see ¶ 101-102). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 15, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the suggestion generated for the user is personalized based on user preferences, historical activity data, and contextual information derived from the sequence of free-living activity data (see ¶ 38, ¶ 46, ¶ 52). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 16, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the sequence of free-living activity data includes physiological data captured from wearable devices, and preprocessing comprises normalizing the physiological data based on user-specific baseline values (see ¶ 59, ¶ 166). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 17, Duffy discloses the method of claim 1, wherein the suggestion is delivered to the user via an application comprising a visual representation of the next experience and an explanation of how the experience enhances the user's personal, professional, or cultural components (see ¶ 61, ¶ 99, ¶ 128, ¶ 147).
Regarding claim 18, Duffy discloses the method of claim 1, further comprising training the machine learning model using labeled sequence of activity data, wherein the labels correspond to predefined categories of personal, professional, or cultural components (see ¶ 120-121).
Regarding claim 19, Duffy discloses the subset of candidate results might use a clustering algorithm to cluster the results (see ¶ 89).
Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the sequence of free-living activity data includes location data, and preprocessing further comprises clustering the location data to identify frequently visited places and their associated activities (see ¶ 14-16, ¶ 82, ¶ 124-125, ¶ 156). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 20, Duffy discloses predicting what items to be of interest to the user based on demographic information (see ¶ 45).
Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein mapping further comprises identifying temporal relationships between successive multidimensional vectors to refine the prediction of the next event (see ¶ 97-99, ¶ 130). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 21, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the suggestion includes a recommendation for a career path, and the recommendation is based on an analysis of the user's professional component values and historical activity patterns (see ¶ 16, ¶ 51, ¶ 74). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 22, Duffy discloses the method of claim 1, wherein preprocessing comprises detecting anomalies in the sequence of free-living activity data, and the anomalies are flagged for exclusion from the feature extraction process (see ¶ 84, ¶ 146, ¶ 165, ¶ 239).
Regarding claim 23, Duffy discloses the method of claim 1, wherein delivery of the suggestion includes an interactive interface that allows the user to provide feedback on relevance and quality of the suggestion (see ¶ 26, ¶ 31, ¶ 38, ¶ 43).
Regarding claim 24, Duffy discloses the method of claim 1, wherein the suggestion is designed to enhance the user's cultural component by recommending activities that involve exposure to new communities, traditions, or languages (see ¶ 66, ¶ 104, ¶ 128).
Regarding claim 25, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the suggestion comprises a type of an activity (see ¶ 82, ¶ 129). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
In addition, claim 25 merely describes the type of activity data is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 26, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein preprocessing includes segmenting the sequence of free-living activity data into time intervals based on user-defined criteria, such as daily routines or activity durations (see ¶ 59, ¶ 65, ¶ 118). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 27, Duffy does not explicitly disclose the following limitations; however, Miller discloses the method of claim 1, wherein the sequence of free-living activity data comprises at least one of sensor data from wearable devices, location data, user interaction data, or social network data (see ¶ 46-47, ¶ 65, ¶ 73). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Duffy and in view of Miller to include the teaching of Feldman in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
In addition, claim 27 merely characterizes the activity data is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 28, Duffy discloses the method of claim 1, wherein the sequence of free-living activity data comprises at least one of sensor data from other users or other systems, wherein the sensor data comprises at least one of activity data, behavior data, location data, purchase data, media content consumed, social media activity, images, or sound data (see ¶ 52, ¶ 128, ¶ 200, ¶ 211).
In addition, claim 28 merely describes the type of sensor data is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 29, Duffy discloses the method of claim 1, wherein the output multidimensional vector includes values for at least one of personal, professional, or cultural components (see ¶ 151, ¶ 168).
In addition, claim 29 merely describes the attributes of the multidimensional vector is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 30, Duffy discloses the method of claim 1, wherein the output multidimensional vector includes values associated with at least one of images, video, sound, or text (see ¶ 66, ¶ 143).
In addition, claim 30 merely describes the attributes of the multidimensional vector is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Christiansen et al., (US 2014/0282153) discloses a system for customizing user online experience by synthesizing a data set that includes information related to an individual user’s personal preferences as well as information related to preferences shared by the user and members of the online social networking community.
Proud et al., (US 2014/0249853) discloses a system for monitoring user profiles biometric information include user’s activities, behaviors, and habit information captured by a wearable device.
Madhavan et al., (US 2015/0120593) discloses a method for recommending learning activities or job to registered users in relation to selected jobs by analyzing key activities that users are engaging in while accessing integrated learning services.
Sarmiento et al., (KR 20160062079 A) discloses a structure based predictive modeling for constructing a sequence activation model and training a sequence activation model using a support vector machine.
Tien Nguyen, “Enhancing User Experience with Recommender System Beyond Prediction Accuracies” A thesis submitted to the faculty of the graduate school of the University of Minnesota, August, 2016.
Xia et al., “Mobile Multimedia Recommendation in Smart Communities: A Survey”, School of Software, Dalian University of Technology, Dalian 116620, China. IEEE Access Volume 1, 2013.
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/PAN G CHOY/Primary Examiner, Art Unit 3624
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