DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 21, 2026 has been entered.
Priority
Examiner has given consideration to applicant’s PCT/JP2022/035 filed on September 21, 2022 and JP2021-153235 filed on September 21, 2021. For examining purposes of this application, the effective filing date will be September 21, 2021.
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55 on March 18, 2024.
Status of the Claims
Claims 1-8 are currently pending and have been considered below.
Claim 1 has been amended.
Response to Arguments
Applicant’s arguments, with respect claim rejection under §112 (b) of claim 1 has been fully considered and is not persuasive. Applicant moved the limitation “a processor and memory storing instructions and configured to implement:” further down in the body of the claim and submits that the amendment obviates the rejection. Applicant does not elaborate as to how the moving of the limitation within the body of claim overcomes the 112(b) rejection. The limitation “a processor and memory storing instructions and configured to implement:” remains unclear and ambiguous as to what its function is within the claim even after the amendment. Therefore, the rejection under §112 (b) has not been overcome.
Applicant's arguments regarding §101 rejection on pages 7-11 have been fully considered but they are not persuasive.
The claimed invention, as a whole, is directed to the abstract idea of collecting user information, determining whether additional information is needed, requesting that information from the user, and updating stored information based on the user’s response. These activities fall within the abstract idea categories of certain methods of organizing human activity and mental processes. More specifically, the claims recite using stored user and facility information to identify missing or insufficient content information, prompting the user to provide additional input, and updating the user profile accordingly. These are fundamental data gathering, analysis, and record updating concepts that may be performed mentally or with pen and paper, and which are implemented here using generic computer components.
Applicant argues that claim 1 recites a specific technical configuration because the storage medium stores facility information including facility ID, coordinates, facility type, number of stores, review data, total number of reviews, and extracted keywords, and because the comparison target is based on other content information stored for other facility types. This argument is not persuasive. The recited information fields merely describe the type of content stored and analyzed. Storing facility-related data, review data, and keywords does not constitute an improvement to computer functionality or to any underlying data structure. Likewise, the limitation that the predetermined comparison target is based on content information for other facility types merely defines a rule for deciding when additional user information should be requested. This is an abstract decision-making criterion directed to content selection and profile completion, not a technical improvement to the operation of a computer or storage system.
Applicant further argues that the claimed cross-facility-type comparison mechanism provides a practical improvement by enabling targeted and efficient data collection. However, improving the completeness or quality of stored recommendation data does not amount to an improvement in computer technology itself. The claims do not recite a new database architecture, a new memory arrangement, a new communication protocol, or any other specific technical solution to a technical problem. Rather, the claims use generic computing components to implement a business or informational workflow for prompting a user to provide more data. Such a result-oriented recitation does not integrate the abstract idea into a practical application.
Applicant’s reliance on Enfish, McRO, and DDR is also unpersuasive. In those cases, the claims were directed to specific technical solutions that improved the functioning of the computer or a technology-based process. Here, the claims merely apply generic computer operations to the abstract task of identifying incomplete user preference information and requesting additional input. The alleged benefit is the improved completeness of recommendations or user profiles, which is not an improvement to computer functionality. Accordingly, the claims are distinguishable from the eligible claims in those cases.
Applicant also argues that claim 2’s recitation of determining requested content based on current position or current time period ties the invention to a specific technical implementation. This argument is not persuasive. Location-based or time-based filtering is a conventional content-selection technique and does not provide a technological improvement. It merely adds another abstract criterion for deciding what information to request from the user.
Under Step 2B, the additional elements do not amount to significantly more than the abstract idea. The claims recite a processor, memory, storage medium, acquisition unit, output unit, update unit, and user device. These elements are described at a high level of generality and perform their ordinary and conventional functions of storing data, receiving information, transmitting prompts, and updating records. The claims do not recite any unconventional hardware, special programming, or non-routine processing that would supply an inventive concept. The specification’s discussion of improved recommendation accuracy and user profile enrichment describes the intended result of the abstract idea, not a technological innovation sufficient to transform the claim into patent-eligible subject matter.
Accordingly, the rejection of claims 1-8 under 35 U.S.C. § 101 is maintained because the claims are directed to an abstract idea and do not include additional elements that amount to significantly more than the judicial exception.
Applicant's arguments regarding §103 rejection on pages 12-15 have been fully considered but they are not persuasive. The applied references, when properly combined, teach or at least suggest the subject matter of the amended claims. Lessin et al. teaches maintaining a user profile, identifying unknown information items, determining a data acquisition value for the unknown information items based on the value of the information to the system and the likelihood of receiving a response, selecting an unknown information item for acquisition, and presenting a corresponding question or prompt to a user device for receipt of responsive information to be stored in the user profile. Perkowitz et al. further teaches deriving user-specific metrics from historical context data across multiple categories and dimensions, including category-based statistics used to characterize user interests and tendencies. Wilson et al. discloses recommendation systems utilizing stored user, venue, reviewer, and content data to generate recommendations based on comparative relationships among categories of data and user affinities.
Accordingly, the recited limitation requiring that the predetermined comparison target be based on an amount of other content information stored for other facility types is considered an obvious variation of the teachings of the cited references. The prior art need not disclose the claimed language verbatim; rather, the issue is whether the claimed subject matter as a whole would have been suggested to one of ordinary skill in the art at the time of the invention. In the present case, the use of cross-category or cross-type information to identify sparse, missing, or insufficient profile data and to selectively prompt the user to supply additional information is a predictable and routine design choice. Lessin expressly teaches threshold-based acquisition of missing information items, and Perkowitz expressly teaches the use of category-based historical data to characterize user interests. In view of these teachings, it would have been obvious to determine a comparison target based on the amount of information stored for other facility types in order to identify which facility type information is insufficient and should be requested from the user.
Applicant’s contention that the cited references fail to disclose the claimed “predetermined comparison target” because they do not expressly recite comparison against “other facility types” is not persuasive. The test under 35 U.S.C. § 103 is not whether the references use Applicant’s exact terminology, but whether the claimed invention would have been obvious to a person of ordinary skill in the art in view of the combined teachings of the prior art. The use of cross-category information to prioritize data acquisition is a known and expected implementation of profile-completion and recommendation techniques. Applicant has not provided persuasive evidence that the claimed comparison target is directed to anything more than an obvious implementation detail of the known process of identifying and requesting missing user information.
Accordingly, the rejection of claims 1-8 under 35 U.S.C. § 103 is maintained.
Claim Rejections - 35 USC § 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 1 recites "a processor and memory storing instructions and configured to implement: " in line 11. However, it is unclear and ambiguous as to how a processor and memory can be configured to "implement" an acquisition unit, an output unit and update unit. A processor and memory can be configured to perform a function like acquire user information, output request information and update information, however as written it is not clear how one skilled in the art can implement an acquisition unit, an output unit and update unit. For examination purposes, Examiner will assume the processor and memory are configured to acquire user information, output request information and update information.
Claim 1 recites the limitation “the one user information” in line 18. There is insufficient antecedent basis for this limitation in the claim.
Claim 2 recites the limitation “the requested content” in lines 3-4. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation “the requested content” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 5 recites the limitation “the requested contents” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation “the requested content” in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation “the user” in line 3. There is insufficient antecedent basis for this limitation in the claim. It is unclear which “user” Applicant is referring to as there is a “similar user” recited in line 2 and there is “a user” recited in claim 1.
Claim 7 recites the limitation “the requested contents” in lines 2-3. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation “the recording medium” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-8 rejected to as being dependent upon rejected claim 1.
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 1-8 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 1-8 are directed to a system (i.e. a machine). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A- Prong 1
Independent claim 1 recites steps that, under their broadest reasonable interpretations, cover certain methods of organizing human activity, e.g. advertising, marketing or sales activities. Specifically, claim 1 recites:
A recommendation system comprising:
a storage medium storing content information related to a plurality of facilities including for each a facility ID, facility coordinates, a facility type, a number of stores corresponding to each facility type, review data for each of the stores at the facility, a total number of reviews for each store at the facility, and a keyword extracted from reviews of plural users;
the storage medium storing data for each of the plural users, the data for each user includes for each facility, the facility type, a degree of interest of the user in the facility type and keywords input by a corresponding user for the facility type;
a processor and memory storing instructions and configured to implement:
a user information acquisition unit that acquires user information indicating a degree of user interest of one user in a content to be provided;
an output unit that outputs request information for requesting the one user to input information related to a content stored in the storage medium in which an amount of information of the content stored for a facility type is less than predetermined comparison target in information for each content stored as the user information, by transmitting the request information to a device of the one user; and
an update unit that updates the one user information on a basis of information input by the one user in response to the request information,
wherein the predetermined comparison target is based on amount of other content information stored in the storage medium for the one user for other facility types different from the facility type for which information is being requested.
But for the recitation of generic computer components like various processor, memory, user information acquisition unit, output unit, storage medium, device and update unit, the italicized functions, when considered as a whole, describe a situation where information is gathered from a user regarding content, the information is stored, more information is requested from user and the stored information is then updated. Accordingly, claim 1 recites an abstract idea in the form of a certain method of organizing human activity.
Dependent claims 2-8 inherit the limitations that recite an abstract idea from their dependence on claim 1, and thus these claims also recite an abstract idea under the Step 2A- Prong 1 analysis. In addition, claims 2-8 recite additional limitations that further describe the abstract idea identified in the independent claims.
Claim 2 recites wherein the request information requested by the output unit includes information as to whether the one user has an interest in the requested content, and the requested content is determined based on a current position of the user device or a current time period. (Advertising, Marketing or Sales Activities)
Claim 3 recites wherein the update unit receives an answer to whether the user has the interest as input data to the user information. (Advertising, Marketing or Sales Activities)
Claim 4 recites wherein the output unit recommends the requested content, and the update unit receives an answer to the recommendation as input data to the user information. (Advertising, Marketing or Sales Activities)
Claim 5 recites wherein in a case where there are a plurality of the requested contents, the output unit requests the user to make the input based on a degree of enrichment of the plurality of requested contents. (Advertising, Marketing or Sales Activities)
Claim 6 recites wherein the user information acquisition unit further acquires user information of a similar user whose interest in the content is similar to the user, and the output unit outputs the request information for requesting the one user to input information related to the requested content in user information of the one user and with user information of another user having data stored in the storage medium in common with the one user. (Advertising, Marketing or Sales Activities)
Claim 7 recites wherein the request information includes information related to the requested content, and
the information related to the requested content includes at least any one of a facility type, a distance to a facility, a facility name, a price range of a facility, or a facility review. (Advertising, Marketing or Sales Activities)
Claim 8 recites wherein the update unit records the information input in the recording medium. (Advertising, Marketing or Sales Activities)
Step 2A-Prong 1: YES. The claims are abstract
Step 2A- Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claim 1 does not include additional elements that integrate the abstract idea into a practical application. The additional elements of claim 1 are processor, memory, user information acquisition unit, output unit, storage medium, device and update unit. These additional elements, when considered in the context of each claim as a whole, merely serve to automate interactions that could occur between human actors (as described above), and thus amount to instructions to “apply” the abstract idea using generic computer components (see MPEP 2106.05(f)). For example, a company could gather information from its customers about products that they sell or intend to sell in the future. They may find out that some information is lacking, so they could request additional information from customers. The additional information could then be compiled with the rest of the information and then business decisions could be made based on the information. Also, the additional elements as listed add insignificant extra-solution activity to the abstract idea. For example, collecting data, requesting data and updating data as seen in claim 1 amounts to mere data gathering and selecting a particular data source or type of data to be manipulated, (see MPEP 2106.05(g)) and Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). Accordingly, claim 1 as a whole is directed to an abstract idea without integration into a practical application.
The judicial exception recited in dependent claims 2-8 are also not integrated into a practical application under a similar analysis as above. The functions of claims 2-8 are performed with the same additional elements introduced in the independent claims, however, even these additional elements amount to instructions to “apply” the abstract idea using generic computer components, (see MPEP 2106.05(f)) and mere data gathering and selecting a particular data source or type of data to be manipulated, (see MPEP 2106.05(g)).
Accordingly, the additional elements of claims 1-8 do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claims 1-8 are directed to an abstract idea.
Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of processor, memory, user information acquisition unit, output unit, storage medium, device and update unit amount to mere instructions to apply the exception using generic computer components. As evidence of the generic nature of the above recited additional elements, Examiner notes paragraphs 10, 11 and 26 and Figure 1 of Applicant’s specification, where the computerized implementations of the system are disclosed in terms of known computer architecture such as processors, software and communications or equivalent hardware. These disclosures do not indicate that the elements of the invention are particular machines, and instead provide generic examples of computer hardware such that one of ordinary skill in the art would understand that any generic processor-based computer device could be used to implement the invention.
Step 2B: NO. The claims do not provide significantly more.
Thus, when considered as a whole and in combination, claims 1-8 are not patent eligible.
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.
Claim(s) 1-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wilson et al., U.S. Patent Application Publication 2020/0184538 (see PTO-892, Ref. E) in view of Lessin et al., U.S. Patent Application Publication 2014/0143325 (see PTO-892, Ref. B) and further in view of Perowitz et al., U.S. Patent Application Publication 2015/0170042 (see PTO-892, Ref. A).
As per claim 1, Wilson teaches a recommendation system comprising:
a storage medium storing content information related to a plurality of facilities including for each a facility ID, facility coordinates, a facility type, a number of stores corresponding to each facility type, review data for each of the stores at the facility, a total number of reviews for each store at the facility, and a keyword extracted from reviews of plural users ((see venue/“facility” attributes and review data; parsing into structured DB ([0040], [0064], [0100]–[0104]); unique IDs, address, lat/long matching ([0183]); review volumes as quality signals ([0058]));
the storage medium storing data for each of the plural users, the data for each user includes for each facility, the facility type, a degree of interest of the user in the facility type and keywords input by a corresponding user for the facility type ((see user profiles (favorites, demographics) and explicit interest feedback (thumbs up/down, ratings) ([0069]–[0071], [0083]–[0086]); type/genre present ([0100]–[0104]));
a processor and memory storing instructions and configured to implement (see paragraphs 48 and 200-204);
a user information acquisition unit that acquires user information indicating an degree of user interest of one a user in a content to be provided (see collects preferences and explicit feedback ([0069]–[0071], [0083]–[0086], [0197]);
Lessin teaches an output unit that outputs request information for requesting the one user to input information related to a content stored in the storage medium in which an amount of information of the content stored for a facility type is less than a predetermined comparison target in information for each content stored as the user information, by transmitting the request information to a device of the one user (identifies unknown/missing (or stale) information items in a user profile; determines data acquisition values; selects questions and formats; and presents questions across multiple channels, with response probabilities used to predict response ([0016]–[0019], [0038]–[0049], [0050]–[0054], [0064])).
an update unit that updates the one user information on a basis of information input by the one user in response to the request information (response module stores the user’s response into the profile, associated with the targeted information item ([0057], [0064]). Wilson also teaches updates repository with user input/feedback ([0195]–[0206])),
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the filing date of the invention to combine the teachings of Wilson and Lessin to implement Wilson’s “gap prompting” using Lessin’s exact mechanism for missing-profile fields: both problems—improving per-user data completeness to improve recommendation quality—are the same. The “predetermined comparison target” in claim 1 is obvious by Lessin’s data-acquisition value computation, which explicitly compares current profile data against a value/need threshold and response probabilities ([0041]–[0046]). One would be motivated because improving per-user data completeness would improve recommendation quality.
Perkowitz teaches wherein the predetermined comparison target is based on amount of other content information stored in the storage medium for the one user for other facility types different from the facility type for which information is being requested (per-user aggregated statistics across categories, distances, familiarity, price, with home/non-home segmentation ([0121]–[0129])).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the filing date of the invention to combine the teachings of Wilson, Lessin and Perkowitz to implement use those per-user cross-type metrics as a benchmark and coupling that with Lessin’s “unknown item” scoring and prompting provides the claimed comparison target logic. It would have been obvious to use the per-user cross-category counts (amounts) as the threshold/target to compare information for less content for that particular user to maximize value of additional data because improving per-user data completeness would improve recommendation quality.
As per claim 2, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Lessin and Perkowitz teach wherein the request information requested by the output unit includes information as to whether the one user has an interest in the requested content, and the requested content is determined based on a current position of the user device or a current time period (Lessin: selects and formats questions to elicit missing/unknown items; can trigger based on user actions and select channels with highest response probability ([0050]–[0054], [0052]) and Perkowitz: context-aware agent uses current position/time to select and present recommendations/agent prompts ([0167]–[0171]); also computes distances and categories ([0120]–[0129])).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the filing date of the invention to combine the teachings of Wilson, Lessin and Perkowitz to trigger Lessin-style gap prompts when Perkowitz indicates the user is at a relevant place/time (e.g., near a venue of the same facility type currently sparse for that user) to maximize utility and response probability (see Lessin, [0045]–[0046]).
As per claim 3, Wilson, Lessin and Perkowitz teach the system of claim 2 as seen above. Lessin teaches wherein the update unit receives an answer to whether the user has the interest as input data to the user information (stores responses in the user’s profile, associated with the targeted information item ([0057], [0064]).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the filing date of the invention to combine the teachings of Wilson, Lessin and Perkowitz to update user data because improving user data completeness would improve recommendation quality.
As per claim 4, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Wilson teaches wherein the output unit recommends the requested content, and the update unit receives an answer to the recommendation as input data to the user information (recommendation engine outputs recommendations; user responses recorded and used to adapt links/models ([0091]–[0097], [0083]–[0086], [0195]–[0206]). Alternatively, Lessin also teaches wherein the output unit recommends the requested content, and the update unit receives an answer to the recommendation as input data to the user information (the targeted item is chosen precisely because it is missing/sparse; presenting it and recording the response are taught ([0016]–[0019], [0038]–[0049], [0057], [0064]). One would be motivated to record the user’s response to enrich the profile (predictable improvement in data quality and personalization).
As per claim 5, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Lessin teaches wherein in a case where there are a plurality of the requested contents, the output unit requests the user to make the input based on a degree of enrichment of the plurality of requested contents (scoring module computes a “data acquisition value” per unknown item that combines value to the system and response probability; selection module picks the highest-valued item or those above a threshold ([0041]–[0049]). This is a prioritization among multiple gaps—i.e., a “degree of enrichment.”). One would be motivated to pick the highest-value item for prioritization because it would lead to predictable improvement in data quality and personalization.
As per claim 6, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Lessin teaches wherein the user information acquisition unit further acquires user information of a similar user whose interest in the content is similar to the user, and the output unit outputs the request information for requesting the one user to input information related to the requested content in user information of the one user and user information of another user having data stored in the storage medium in common with the one user (can use responses and behavior of users connected to the target user to estimate response probability and can route/format questions accordingly ([0045]–[0046], [0054] (prompting another/connected user)).
It would have been obvious to consider a “similar user” (friend/cohort) when identifying shared unknowns and to prompt the target user because the same item is missing or low-confidence for the cohort—this leverages social/context cues to raise response probability, as taught by Lessin ([0045]–[0046], [0054]).
As per claim 7, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Wilson further teaches wherein the request information includes information related to the requested content, and the information related to the requested content includes at least any one of a facility type, a distance to a facility, a facility name, a price range of a facility, or a facility review (all enumerated fields are present (genre/type, name, price, and location/distance via neighborhood/GPS), and reviews are harvested/parsed ([0100]–[0104], [0115]–[0146], [0040], [0064], [0095]–[0097]).
As per claim 8, Wilson, Lessin and Perkowitz teach the system of claim 1 as seen above. Wilson further teaches wherein the update unit records the information input in the recording medium (updates persistent data repository with user inputs/feedback ([0195]–[0206])).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAHID R MERCHANT whose telephone number is (571)270-1360. The examiner can normally be reached M-F 7:30-5.
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, Namrata Boveja can be reached at 571-272-8105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
Prosecution Insights