DETAILED ACTION
Status of Claims
Claims 1-20 are currently pending and have been examined in this application. This communication is the first action on the merits.
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 .
Claim Objections
Claims 2-3, 7, 11-12, 14, 16-17, and 19 are objected to because of the following informalities:
Claims 2, 11, and 16: “receiving an input dataset including, at least one of a user’s historical communication data and the user information; predicting, the one or more suggested group activities, that one of the one or more users is likely to attend based on the input dataset; and producing, an output dataset comprising the one or more suggested group activities, that one of the one or more users is likely to attend” should read “receiving an input dataset including at least one of a user’s historical communication data and the user information; predicting the one or more suggested group activities that one of the one or more users is likely to attend based on the input dataset; and producing an output dataset comprising the one or more suggested group activities that one of the one or more users is likely to attend” (unnecessary commas removed after the bolded italicized words);
Claims 3, 12, and 17: “receiving an input dataset including, user information of a plurality of user profiles… and producing, an output dataset…” should read “receiving an input dataset including user information of a plurality of user profiles… and producing an output dataset…” (unnecessary commas removed after the bolded italicized words);
Claims 7, 14, and 19: “receiving an input dataset including, user information of a plurality of user profiles” should read “receiving an input dataset including user information of a plurality of user profiles” (unnecessary commas removed after the bolded italicized words).
Appropriate correction is required.
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 an abstract idea without significantly more.
Step 1
Claims 1-9 are directed to a machine. Claims 10-14 are directed to a process. Claims 15-20 are directed to an article of manufacture. As such, each claim is directed to a statutory category of invention.
Step 2A Prong 1
The examiner has identified independent Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent Claims 10 and 15.
Independent Claim 1 recites the following abstract ideas: “identifying and facilitating communication and networking: receive a user profile, the user profile including user information, wherein the user information is comprised of at least one of one or more user interests, one or more user preferences, or membership to one or more private communities; createone or more hangouts based on the user information, wherein the one or more hangouts include at least one of one or more public hangouts, one or more exclusive hangouts, or one or more private hangouts, wherein the one or more exclusive hangouts restrict a user’s ability to join the one or more exclusive hangouts, wherein each of the one or more private hangouts are associated to one or more private communities, and wherein the one or more private hangouts are configured to be accessible to users having membership to the one or more associated private communities or users invited to the one or more private hangouts by an organizing user; displaythe one or more hangouts on a map , wherein the map is configured to display a geographical representation of an approximate location of the one or more hangouts; receivea request to join one of the one or more exclusive hangouts from one of the one or more users, upon approval of the request, generating a environment; createone or more suggested group activities; determinecompatibility scores between a first user and one or more additional users; and display to the first user one or more indicators identifying one or more of, the one or more additional users associated with a compatibility score which is above a compatibility score threshold.”
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, relates to managing relationships or interactions between people including social activities (i.e., identifying and facilitating communication and networking: receive a user profile, the user profile including user information, wherein the user information is comprised of at least one of one or more user interests, one or more user preferences, or membership to one or more private communities; create one or more hangouts based on the user information, wherein the one or more hangouts include at least one of one or more public hangouts, one or more exclusive hangouts, or one or more private hangouts, wherein the one or more exclusive hangouts restrict a user’s ability to join the one or more exclusive hangouts, wherein each of the one or more private hangouts are associated to one or more private communities, and wherein the one or more private hangouts are configured to be accessible to users having membership to the one or more associated private communities or users invited to the one or more private hangouts by an organizing user; display the one or more hangouts on a map, wherein the map is configured to display a geographical representation of an approximate location of the one or more hangouts; receive a request to join one of the one or more exclusive hangouts from one of the one or more users, upon approval of the request, generating a environment; create one or more suggested group activities; determine compatibility scores between a first user and one or more additional users; and display to the first user one or more indicators identifying one or more of, the one or more additional users associated with a compatibility score which is above a compatibility score threshold), but for the recitation of generic computer components (i.e., a system comprising a device comprising at least one device processor, at least one device database, at least one device memory comprising computer-executable device instructions, virtual communication, a user profile module, a hangout creation module, a display module, an interface, a user request module, a virtual environment, a communication module, a suggestion algorithm, and a connection algorithm). If a claim limitation, under its broadest reasonable interpretation, relates to managing relationships or interactions between people including social activities, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). In particular, the claim recites the additional elements of a system comprising a device comprising at least one device processor, at least one device database, at least one device memory comprising computer-executable device instructions, virtual communication, a user profile module, a hangout creation module, a display module, an interface, a user request module, a virtual environment, a communication module, a suggestion algorithm, and a connection algorithm (in addition to the non-transitory CRM of Claim 15). The computer hardware is recited at a high level of generality (i.e., generic computers and computer modules and algorithms receiving, generating, and displaying information, a generic interface for displaying information, and a generic virtual environment) such that it amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application, since they do not involve improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)), they do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and they do not apply or use the abstract idea in some other meaningful way beyond generally linking its use to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e)). Therefore, the claim is directed to an abstract idea without a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. The additional elements of using computer hardware (a system comprising a device comprising at least one device processor, at least one device database, at least one device memory comprising computer-executable device instructions, virtual communication, a user profile module, a hangout creation module, a display module, an interface, a user request module, a virtual environment, a communication module, a suggestion algorithm, and a connection algorithm (in addition to the non-transitory CRM of Claim 15)) amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claim is not patent-eligible.
Dependent claims 2-3, 7, 11-12, 14, 16-17, and 19 recite a “machine learning algorithm,” which is recited at a high level of generality, as a generic ML algorithm receiving, determining, and outputting information. Dependent claims 6, 13, and 18 recite a “smart invite algorithm,” which is recited as a generic algorithm sending information. The additional elements are generic technology used to implement the abstract idea, and they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Dependent claims 4-6, 8-9, 13, 18, and 20 do not include any additional elements beyond those identified above. They further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. As such, they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Therefore, dependent claims 2-9, 11-14, and 16-20 are directed to an abstract idea, and do not include additional elements that integrate the abstract idea into a practical application, or that are sufficient to amount to significantly more than the abstract idea. Thus, the aforementioned claims 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.
Claims 1, 4-6, 8-10, 13, 15, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Baldwin et al. (US-20140047023) in view of Boyd et al. (US-20210336916).
Claim 1 (and Similarly Claims 10 and 15)
Baldwin teaches the following limitations:
A system for identifying and facilitating virtual communication and networking, the system comprising: a device comprising at least one device processor, at least one device database, at least one device memory comprising computer-executable device instructions which, when executed by the at least one device processor, cause the device to: receive a user profile, via a user profile module, the user profile including user information, wherein the user information is comprised of at least one of one or more user interests, one or more user preferences, or membership to one or more private communities ([0011] Users of the social networking system may provide personal information to the social networking system, which is stored in user profiles. For example, a user may provide age, gender, geographical location, education history, employment history and the like; [0034] the set of candidate users includes users that have likes, activities, status messages, or stated interests that correspond to a topic or category associated with the event; [0042] The suggestion module 235 accesses 305 a user object associated with the inviting user. The accessed user object describes attributes of the inviting user, such as interests, gender, age, current location, hometown, educational history, employment history or other data describing the inviting user);
create, via a hangout creation module, one or more hangouts based on the user information, wherein the one or more hangouts include at least one of one or more public hangouts, one or more exclusive hangouts, or one or more private hangouts, wherein the one or more exclusive hangouts restrict a user’s ability to join the one or more exclusive hangouts, wherein each of the one or more private hangouts are associated to one or more private communities, and wherein the one or more private hangouts are configured to be accessible to users having membership to the one or more associated private communities or users invited to the one or more private hangouts by an organizing user ([0011] The data provided by a user may be used by the social networking system, along with other data, to generate useful suggestions for presentation to the user. For example, the social networking system uses the provided data along with other social networking system information to suggest additional users for a user to invite to an event. The user may be any user authorized to invite other users to the event, such as an event creator or an event host, a promoter or a user invited to the event with the authority to invite additional users; [0034] the suggestion module 235 may use other attributes of the users connected to the inviting user and the event to select the set of candidate users. For example, the set of candidate users includes users that have likes, activities, status messages, or stated interests that correspond to a topic or category associated with the event. For instance, if the event is an automobile race, the candidate users include users that have indicated an interest in automobile racing, that have liked pages related to automobile racing, that have posted status messages related to automobile racing topics, or have participated in activities related to automobile racing in the past (e.g. attending automobile racing events));
create, via a suggestion algorithm, one or more suggested group activities ([0011] the social networking system uses the provided data along with other social networking system information to suggest additional users for a user to invite to an event; [0042] the suggestion module 235 identifies additional users connected to the inviting user and one or more events connected to the inviting user. The suggestion module 235 identifies one or more event objects connected to the accessed event object and selects 310 an event allowing the inviting user to invite additional users);
determine, via a connection algorithm, compatibility scores between a first user and one or more additional users ([0035] The suggestion module 235 also uses affinity scores between the inviting user and candidate users to determine which candidate users to select. The affinity score represents the likely interest in a candidate user by the inviting user. In some embodiments, the affinity scores also account for characteristics of the event, as well as the inviting user and a candidate user. An affinity score between the event and a candidate user represents the likely interest in the event by a candidate user. A candidate user may be selected based on both an affinity score between the candidate user and the event and an affinity score between the candidate user and the inviting user. For instance, a weighted sum of the affinity score between a candidate user and the event, and the affinity score between a candidate user and the inviting user may be used to select a candidate user. The weighting of the affinity scores may be adjusted to emphasize the interest in a candidate user by the inviting user, or the interest in the event by a candidate user; [0045] the affinity of the inviting user for different users connected to the inviting user may be used to select 320 the candidate users for which the inviting user has the highest affinity); and
display to the first user one or more indicators identifying one or more of, the one or more additional users associated with a compatibility score which is above a compatibility score threshold ([0046] the suggestion module 235 bases the prediction of a candidate user joining the event on one or more of the candidate user's affinity score for the inviting user, the candidate user's location relative to the event's location and the candidate user's availability at the time of the event. The suggestion module 235 may select 325 candidate users having scores indicating at least a threshold probability, or likelihood, of attending the event if invited to the event; [0049] The suggestion module 235 identifies 330 the one or more selected candidate users to the inviting user, allowing the inviting user to determine whether to invite one or more of the selected candidate users to the event. The selected candidates may be identified to the inviting user by sending a notification to a client device 105 associated with that user).
However, Baldwin does not explicitly teach the following limitations:
display, via a display module, the one or more hangouts on a map interface, wherein the map interface is configured to display a geographical representation of an approximate location of the one or more hangouts;
receive, via a user request module, a request to join one of the one or more exclusive hangouts from one of the one or more users, upon approval of the request, generating a virtual environment, via a communication module;
Boyd, in the same field of endeavor, teaches the following limitations:
display, via a display module, the one or more hangouts on a map interface, wherein the map interface is configured to display a geographical representation of an approximate location of the one or more hangouts ([0115] the interactive map section 1108 displays an indication of the event on the map (not shown) at a location corresponding to the event);
receive, via a user request module, a request to join one of the one or more exclusive hangouts from one of the one or more users ([0114] once a user has created the event overlay component 704 and invited other users, or once a user has received and interactively joined the event associated with the event overlay component 704, the modified event overlay component 906 as shown, displays a generated status notification icon 1102, and one or more avatars 910 associated with each user that has received the event overlay component 704 and has interactively joined the event after accessing the interactive join option 912 displayed in the extended separate section 914 of the event overlay message interface 908), upon approval of the request, generating a virtual environment, via a communication module ([0116] The message section 1110 contains a chat session between users that have joined the event, in which a user joining an event can view messages in the chat session that occurred after the user joined the event; [0124] when a user joins the event, the user gains access to an event chat interface, such as the event chat interface 1304 shown in FIG. 13A);
This known technique is applicable to the system of Baldwin as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Boyd would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Boyd to the teachings of Baldwin would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., displaying an event with a location on a map, providing an online environment for event attendees to communicate) into similar systems.
Claim 4 (and Similarly Claim 20)
Boyd further teaches the following limitations:
wherein the virtual environment is a chat facilitating real-time communication amongst the one or more users ([0116] The message section 1110 contains a chat session between users that have joined the event, in which a user joining an event can view messages in the chat session that occurred after the user joined the event; [0124] when a user joins the event, the user gains access to an event chat interface, such as the event chat interface 1304 shown in FIG. 13A).
This known technique is applicable to the system of Baldwin as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Boyd would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Boyd to the teachings of Baldwin would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing a real-time chat for event attendees to communicate) into similar systems.
Claim 5
Baldwin further teaches the following limitations:
wherein the one of one or more user interests and one or more user preferences include at least one of: outdoor activities, indoor activities, sports, religion, and education ([0042] The accessed user object describes attributes of the inviting user, such as interests... educational history; [0034] the set of candidate users includes users that have likes, activities, status messages, or stated interests that correspond to a topic or category associated with the event. For instance, if the event is an automobile race, the candidate users include users that have indicated an interest in automobile racing).
Claim 6 (and Similarly Claims 13 and 18)
Baldwin further teaches the following limitations:
wherein the computer-executable device instructions which, when executed by the at least one device processor, further cause the device to: send, via a smart invite algorithm, invites to one or more suggested users that are likely to attend the one or more hangouts, the invites corresponding to the one or more hangouts ([0004] To aid an inviting user in inviting additional users to an event, the social networking system may suggest users for inviting to the event. The social networking system may determine the suggested users based on the likelihood that the suggested users will accept an invitation to an event).
Claim 8
Baldwin further teaches the following limitations:
wherein the computer-executable device instructions which, when executed by the at least one device processor, further cause the device to: enable, via a contextual invite system, a first user to invite a second user to join one of the one or more hangouts ([0006] The inviting user is then notified of the selected one or more candidate users, allowing the inviting user to invite the selected one or more candidate users to the event).
Claim 9
Baldwin further teaches the following limitations:
wherein the contextual invite system is based on at least one of a proximity to the first user and a community membership of the second user ([0004] To aid an inviting user in inviting additional users to an event, the social networking system may suggest users for inviting to the event… In making this determination, the social networking system may use a variety of factors, such as the location and availability of the suggested users in view of the time and location identified by the event).
Claims 2-3, 7, 11-12, 14, 16-17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Baldwin et al. (US-20140047023) in view of Boyd et al. (US-20210336916), and further in view of Baldwin et al. (US-20140089320).
Claim 2 (and Similarly Claims 11 and 16)
Baldwin (‘023) further teaches the following limitations:
wherein the suggestion algorithm is a… algorithm including a computer-implemented method comprising: receiving an input dataset including, at least one of a user’s historical communication data and the user information ([0006] Other factors may be used in predicting whether a candidate user would join the event. For example, the location and/or availability of the candidate user at the time the event is scheduled to occur, and a history of a candidate user and the inviting user attending the same events provides an indication of whether the user is likely to accept the invitation to the event);
predicting, the one or more suggested group activities, that one of the one or more users is likely to attend based on the input dataset ([0006] Other factors may be used in predicting whether a candidate user would join the event. For example, the location and/or availability of the candidate user at the time the event is scheduled to occur, and a history of a candidate user and the inviting user attending the same events provides an indication of whether the user is likely to accept the invitation to the event; [0042] the suggestion module 235 identifies additional users connected to the inviting user and one or more events connected to the inviting user. The suggestion module 235 identifies one or more event objects connected to the accessed event object and selects 310 an event allowing the inviting user to invite additional users); and
producing, an output dataset comprising the one or more suggested group activities, that one of the one or more users is likely to attend ([0011] The data provided by a user may be used by the social networking system, along with other data, to generate useful suggestions for presentation to the user; [0042] the suggestion module 235 identifies additional users connected to the inviting user and one or more events connected to the inviting user. The suggestion module 235 identifies one or more event objects connected to the accessed event object and selects 310 an event allowing the inviting user to invite additional users).
However, Baldwin (‘023), in combination with Boyd, does not explicitly teach the following limitations:
wherein the suggestion algorithm is a machine learning algorithm
Baldwin (‘320), in the same field of endeavor, teaches the following limitations:
wherein the suggestion algorithm is a machine learning algorithm ([0038] to suggest events for a target user to attend, the suggestion generator 300 selects a pool of candidate events based on information about the target user and information about various events. Information used for selection of candidate events may include event location, event attendee information, event organizer information, the target user's location, descriptive data associated with the event, the target user's interests, etc. The suggestion generator 300 calculates a score for each of the candidate events based on the target user's characteristics and characteristics of each of the candidate events. The scores provide a measure of how likely the target user would be interested in the various candidate events. In one implementation the candidate events are scored using machine-learned models)
This known technique is applicable to the system of Baldwin (‘023), in combination with Boyd, as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms that determine suggested events based on user information. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Baldwin (‘320) would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Baldwin (‘320) to the teachings of Baldwin (‘023), in combination with Boyd, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., determining the suggested activities using machine learning) into similar systems.
Claim 3 (and Similarly Claims 12 and 17)
Baldwin (‘023) further teaches the following limitations:
wherein the connection algorithm is a… algorithm including a computer-implemented method comprising: receiving an input dataset including, user information of a plurality of user profiles ([0034] the set of candidate users includes users that have likes, activities, status messages, or stated interests that correspond to a topic or category associated with the event; [0042] The accessed user object describes attributes of the inviting user, such as interests, gender, age, current location, hometown, educational history, employment history or other data describing the inviting user);
determining a similarity between the user information of a first user and the user information of the one or more additional users ([0037] the suggestion module 235 determines shared interests between the inviting user and a candidate user based on information in the user profiles for the respective users and/or actions taken by the users); and
producing, an output dataset including the compatibility score of the first user and the one or more additional users ([0035] The suggestion module 235 also uses affinity scores between the inviting user and candidate users to determine which candidate users to select. The affinity score represents the likely interest in a candidate user by the inviting user. In some embodiments, the affinity scores also account for characteristics of the event, as well as the inviting user and a candidate user. An affinity score between the event and a candidate user represents the likely interest in the event by a candidate user. A candidate user may be selected based on both an affinity score between the candidate user and the event and an affinity score between the candidate user and the inviting user. For instance, a weighted sum of the affinity score between a candidate user and the event, and the affinity score between a candidate user and the inviting user may be used to select a candidate user. The weighting of the affinity scores may be adjusted to emphasize the interest in a candidate user by the inviting user, or the interest in the event by a candidate user).
However, Baldwin (‘023), in combination with Boyd, does not explicitly teach the following limitations:
wherein the connection algorithm is a machine learning algorithm
Baldwin (‘320), in the same field of endeavor, teaches the following limitations:
wherein the connection algorithm is a machine learning algorithm ([0047] The candidate filter 315 may cluster the target user with other users of the social networking system to discover additional users similar to the target user. The candidate filter 315 then uses historical data describing events attended by these similar users to select 415 candidate events for the target user... A machine-learned model may be used in both the clustering and similarity-based selection)
This known technique is applicable to the system of Baldwin (‘023), in combination with Boyd, as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms that determine similarity between user information of different users. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Baldwin (‘320) would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Baldwin (‘320) to the teachings of Baldwin (‘023), in combination with Boyd, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., determining similarity between users using machine learning) into similar systems.
Claim 7 (and Similarly Claims 14 and 19)
Baldwin (‘023) further teaches the following limitations:
wherein the smart invite algorithm is a… algorithm including a computer-implemented method comprising: receiving an input dataset including, user information of a plurality of user profiles ([0034] the set of candidate users includes users that have likes, activities, status messages, or stated interests that correspond to a topic or category associated with the event; [0042] The accessed user object describes attributes of the inviting user, such as interests, gender, age, current location, hometown, educational history, employment history or other data describing the inviting user);
predicting the one or more suggested users that are likely to attend the one or more hangouts ([0037] The likelihood of a candidate user attending an event may be determined based on various factors... the suggestion module 235 determines shared interests between the inviting user and a candidate user based on information in the user profiles for the respective users and/or actions taken by the users. The suggestion module 235 may determine that a candidate user with a number of types of interests in common with the inviting user is likely to attend an event that the inviting user created or is attending. For instance, the inviting user and a candidate user may both share a common stated interest in several films and TV shows, and based on this commonality the suggestion module 235 may determine that the likelihood of the candidate user accepting an invitation to a film event, from the inviting user, is high); and
producing an output dataset comprising the one or more suggested users ([0006] One or more users may be selected from the set of candidate users based on a prediction of whether a suggestion to invite a candidate user would lead to the invited candidate user joining the event).
However, Baldwin (‘023), in combination with Boyd, does not explicitly teach the following limitations:
wherein the smart invite algorithm is a machine learning algorithm
Baldwin (‘320), in the same field of endeavor, teaches the following limitations:
wherein the smart invite algorithm is a machine learning algorithm ([0048] The score generator 320 generates 420 a relevance score for each of the candidate events. The relevance score associated with a candidate event represents a probability that the target user would accept an invitation to the candidate event. The relevance score may be generated using a machine-learned model that has been trained by the ML training module 310 using historical data about social networking system users' event attendance)
This known technique is applicable to the system of Baldwin (‘023), in combination with Boyd, as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms that users likely to attend an event. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Baldwin (‘320) would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Baldwin (‘320) to the teachings of Baldwin (‘023), in combination with Boyd, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., determining users likely to attend an event using machine learning) into similar systems.
Conclusion
The prior art made of record and not relied upon, considered pertinent to applicant’s disclosure or directed to the state of art, is listed on the enclosed PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARMA EL-CHANTI whose telephone number is (571)272-3404. The examiner can normally be reached T-Sa 10am-6pm ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah Monfeldt can be reached at (571)270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KARMA A EL-CHANTI/Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629