DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Application
Claims 1-20 are pending and have been examined in this application. This communication is the first action on the merits. The Information Disclosure Statement (IDS) filed on December 4, 2024 has been acknowledged.
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 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter. Specifically, claims 1-20 are directed toward at least abstract idea without significantly more. In accordance with MPEP § 2106, the rationale for this determination is explained below.
Representative claim 1 is directed towards a method, claim 13 is directed towards a system, claim 20 is directed towards a non-transitory medium, which are statutory categories of invention.
Although, claim 1 is directed toward a statutory category of invention, the claim however, is directed towards a judicial exception namely an abstract idea. The limitations that set forth the abstract idea recites: collecting explicit user data relating to a user associated with an in-person event; extrapolating implicit user data relating to the user from user interactions and content engagement patterns of the user; generating a user profile for the user by integrating the explicit user data with the implicit user data; dynamically updating the user profile based on real-time data; and generating, via a matchmaking algorithm, a professional match recommendation for the user based on the user profile and one or more additional user profiles of one or more additional users, wherein the professional match recommendation suggests the user professionally network with a different user having one or more attributes that are complementary to the user. These limitations, comprise commercial interactions including, marketing or sales activities; business relations; and managing personal behavior including following rules or instructions. As such, the limitations are directed towards the abstract grouping of Certain Methods of Organizing Human Activity in prong one of step 2A of the Alice/Mayo test (see MPEP 2106.04(a)(2) II).
This judicial exception is not integrated into a practical application because, when analyzed as a whole under prong two of step 2A of the Alice/Mayo test (see MPEP 2106.04(d)), the additional elements provided by the claim amount to merely using a computer as a tool to apply an abstract idea. In particular the claim recites the additional elements: utilizing one or more machine learning models, which is the mere use of a computer as a tool to perform the abstract ideas, see MPEP 2106.05(f). Simply applying the abstract idea by a computer is not a practical application of the abstract idea. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claim is directed to an abstract idea.
The claim does 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 claim recites the additional limitations of a machine learning model, a processor and memory (claim 13), which do not constitute significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment1. Viewing these limitations as a combination, the additional elements amount to no more than merely applying the exception using generic computer components, executing ordinary functions of a computer. Merely applying an exception using generic computer components cannot provide an inventive concept. See TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept). Therefore, the limitations of the claim as a whole, when viewed individually and as an ordered combination, do not amount to significantly more than the abstract idea.
A review of dependent claims 2-12, likewise, do not recite any limitations that would remedy the deficiencies outlined above. The claims only further add to the abstract idea, with no elements which integrate the abstract idea into a practical application or constitute significantly more. Further still, claims 13-20 suffer from substantially the same deficiencies as outlined with respect to claims 1-12 and are also rejected accordingly.
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 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, 3- 5, 8-13 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Byrne (US Publication 2020/0252431) in view of Willis (US Publication 2014/0372328).
A. In regards to Claim 2, Byrne teaches method, system and non-transitory medium, comprising:
a processor; Byrne [0004];
and a non-transitory processor-readable memory device storing instructions that when executed by the at least one processor causes the at least one processor to perform operations including: Byrne [0073];
collecting explicit user data relating to a user associated with an in-person event; Byrne [0021: data sources may also include event attendance database, comprising user profile data derived from lists of attendees at relevant events, such as technical meetings or training events];
extrapolating implicit user data relating to the user from user interactions and content engagement patterns of the user; Byrne [0022: data sources may include work assignment database, comprising user profile data derived from records of work assignments performed by system users and associated interactions];
generating a user profile for the user by integrating the explicit user data with the implicit user data; Byrne [0023: as the skilled person will appreciate, any combination of the above example data sources and any other suitable data sources for deriving user profile data relating to system users, may be used in example implementations of the present disclosure, according to application and/or user requirements];
dynamically updating the user profile based on real-time data; Byrne [0023: the user profile data in the data sources are dynamically updated over time, for example to add new system users and/or new user profile data, or to remove system users (as soon as profile data changes)];
Byrne does not specifically disclose, and generating, via a matchmaking algorithm utilizing one or more machine learning models, a professional match recommendation for the user based on the user profile and one or more additional user profiles of one or more additional users, wherein the professional match recommendation suggests the user professionally network with a different user having one or more attributes that are complementary to the user. This is disclosed by Willis [0073: one or more other employees having some connection to the user's profile information are identified (e.g., by applying one or more similarity algorithms to identify other similar employees), recommendations engine may search the other employees' profile information and/or activity on the professional community's social network to identify information to recommend to the user; recommendations engine may recommend that the user follow the other employee or consider the other employee a role model. However, these are only examples; it should be appreciated that aspects of the invention are not limited to any of the particular examples].
It would have been obvious before the effective filing date of the invention for one of ordinary skill in the art to have modified the teachings of Byrne with the teachings from Willis with the motivation to collect profile information provided by an employee via an interface, which may be aggregated with other profile information stored and or maintained by a profile manager, and recommendations may then be made based on the total aggregated profile information. Willis [0058].
B. In regards to Claims 2 and 14, Byrne does not specifically disclose, wherein the one or more machine learning models include one or more deep learning models. This is disclosed by Willis [0072: similarity algorithms include pattern matching algorithms, k-means clustering algorithms, fuzzy k-means clustering algorithms, Euclidean neighborhood algorithms]. The motivation being the same as stated in claim 1
C. In regards to Claims 4 and 16, Byrne discloses, wherein the real-time data includes at least one of user preferences of the user, user feedback from the user, communication patterns of the user, or emerging industry or professional trends in an industry or profession relevant to the user. Byrne [0038: the method of FIG. 2 uses multiple data sources to derive use profile data associated with system users. The use of multiple data sources, rather than a single data source, provides additional flexibility to define additional or alternative rules and combinations of rules as criteria in rulesets for different contexts; since the user profile data in each of the multiple data sources typically change over time, the method of FIG. 2 may be used to dynamically recalculate, and thus refine and update, the subset of system users permitted automatic access; 0070: ruleset may be updated based on the identified trends, to enable automatic access by such system users in future].
D. In regards to Claim 5, Byrne discloses, further comprising: identifying one or more intricate patterns and correlations across the user profile and the one or more additional user profiles. Byrne [0020: social interactions database comprising user profile data derived from monitoring communications between users such as email, webchat and telephone communications. Historical activity database and social interactions database may define values of properties (i.e., data attributes) associated with interactions of system users, such as membership of a group or network].
E. In regards to Claims 7 and 17, Byrne discloses, further comprising: utilizing the one or more machine learning models to predict emerging industry or professional trends in an industry or profession relevant to the user. Byrne [0070: through the use of machine learning and multiple sources of user data, trends may be identified through exceptions providing override access to different system users in a particular context].
Claims 3-4, 6, 8-13 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Byrne (US Publication 2020/0252431) in view of Willis (US Publication 2014/0372328) in further view of Larsen (US Publication 2026/0010923).
A. In regards to Claims 3 and 15, Byrne does not specifically disclose, wherein the one or more deep learning models include one or more large language models (LLMs). This is disclosed by Larsen [0035: natural language processing model component may be particularly configured for implementing one or more language models, such as term frequency inverse document frequency (TF-IDF), Bidirectional Encoder Representations from Transformers (BERT), Generative Pre-trained Transformer 2 (GPT2), Robustly Optimized BER].
It would have been obvious before the effective filing date of the invention for one of ordinary skill in the art to have modified the teachings of Byrne with the teachings from Larsen with the motivation to provide a means for managing organization dynamics, employee results, customized experience tracks, employee/user reminders, post-event updates and meetups, social media marketing, biometric data, customized engagement management; and permit users to update their profile information, upload documents, and input user preferences/settings. Larsen [0068].
B. In regards to Claims 4 and 16, Larsen additionally and/or alternatively disclose, wherein the real-time data includes at least one of user preferences of the user, user feedback from the user, communication patterns of the user, or emerging industry or professional trends in an industry or profession relevant to the user. Larsen [0018: real-time feedback can be received and evaluated, such as sentiment data indicative of sentiment of the plurality of participants during the event]. The motivation being the same as set forth in claim 3.
C. In regards to Claim 6, Byrne does not specifically disclose, wherein the implicit user data includes user behaviors and user preferences of the user. This is disclosed by Larsen [0031: database(s) stores various (encrypted) data, including user activity data, user preferences data, engagement event content, and artificial intelligence/machine learning training data that can be modified and leveraged by server system]. The motivation being the same as set forth in claim 3.
D. In regards to Claim 8, Byrne does not specifically disclose, further comprising: collecting user feedback from the user; and refining the matchmaking algorithm based on the user feedback. This is disclosed by Larsen [0009: server system may receive feedback from the one or more users and fine-tune the natural language processing model based on the feedback from the one or more user]. The motivation being the same as set forth in claim 3.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Byrne (US Publication 2020/0252431) in view of Willis (US Publication 2014/0372328) in further view of Meyssami (US Publication 2009/0132345).
A. In regards to Claim 9, Byrne does not specifically disclose, wherein the one or more additional users are associated with the same event or a similar event. This is disclosed by Meyssami [0138: system preferably forwards a message to attendees indicating a number of other users that are most similar in user profiles to the particular attendee, and optionally enables the attendee receiving the message to engage the connections].
It would have been obvious before the effective filing date of the invention for one of ordinary skill in the art to have modified the teachings of Byrne with the teachings from Meyssami with the motivation to provide for the creation and updating of meta-profiles in communities which allows for understanding the interests and behaviors of users in a marketplace, by providing recommendations to such users, and for qualifying leads. Meyssami [0146].
B. In regards to Claim 11, Byrne does not specifically disclose, further comprising: scheduling a meeting or other networking activity between the user and the different user. This is disclosed by Meyssami [0138: system preferably forwards a message to attendees indicating a number of other users that are most similar in user profiles to the particular attendee, and optionally enables the attendee receiving the message to engage the connections; 0008: registering a large number of diverse users, the probability increases that a business development executive will be able to find a chain of contacts to a specific person at a specific company whom they would like to meet or talk with in order to explore a potential business relationship]. The motivation being the same as set forth in claim 9.
C. In regards to Claim 12, Byrne discloses, wherein the user is present at the event. Byrne [0079: ech attendee in a trade show environment, along with certain behaviors of each such member, against that set of criteria which in turn is used to determine a qualitative score for such member as a lead for the user]. The motivation being the same as set forth in claim 9.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Byrne (US Publication 2020/0252431) in view of Willis (US Publication 2014/0372328) in further view of Samuel (US Publication 2014/0279034).
A. In regards to Claim 10, Byrne does not specifically disclose, further comprising: generating an interactive location-based heatmap of the event for display to the user, wherein the heatmap shows the location of the different user. This is disclosed by Samuel [0034: heat map module may use GPS mapping that may identify locations that are trending with respect to volume of guests and activity, and/or identify locations where people of user-specified interest are congregating, for example; the musing module may provide a search function for querying a % match to one or more other users for different criteria; the scan artist module may include features that may leverage the camera feature of a smart phone to scan a location for other users that may be identified by an icon that may be clicked-on for information about the other users/venues; and the intel module may provide specific relevant information regarding locations].
It would have been obvious before the effective filing date of the invention for one of ordinary skill in the art to have modified the teachings of Byrne with the teachings from Samuel with the motivation to provide a heat map that lists places the user frequents and/or places that are trending along with the number of the user's contacts at such places [0039].
Conclusion
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Errol CARVALHO whose telephone number is (571) 272-9987. The Examiner can normally be reached on M-F 9:30-7:00 Alt Fri.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ilana Spar can be reached on 571-270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/E CARVALHO/
Primary Examiner, Art Unit 3622
1 See, Alice Corp. Pty Ltd. v. CLS Bank lnt'l, 134 S. Ct. 2347, 2360 (2014) (noting that none of the hardware recited “offers a meaningful limitation beyond generally linking ‘the use of the [method] to a particular technological environment,’ that is, implementation via computers” (citing Bilski v. Kappos, 561 U.S. 593, 610-11 (2010))).