DETAILED ACTION
Introduction
1. This office action is in response to Applicant's submission filed on 02/24/2025. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-16 were previously cancelled and claims 17-36 are currently pending and examined below.
Drawings
2. The drawings filed on 02/24/2025 have been accepted and considered by the Examiner.
Information Disclosure Statement
3. The Information Statement (IDS) filed on 07/28/2025 has been accepted and considered in this office action and it is in compliance with the provisions of 37 CFR 1.97.
Priority
4. The Applicants priority to United States Provisional Application # 62/520486, filed June 15, 2017, has been accepted and considered in this office action.
Double Patenting
5. The non-statutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper time-wise extension of the "right to exclude" granted by a patent and to prevent possible harassment by multiple assignees. A non-statutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Omum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed e-terminal disclaimer (e-TD) in compliance with 37 CFR 1.321 (c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a non-statutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. Effective January 1, 1994, a registered attorney or agent of record may sign an e-terminal disclaimer. An e-terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claim 17-36 of the instant Application are rejected on the ground of non-statutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent # 11651165. Although the conflicting claims are not identical, they are not patentably distinct from each other because the claims of the present application are broader in scope than those of U.S. Patent # 11651165 and hence the claims of U.S. Patent # 11651165 can anticipate those of the present invention. That is, the claims of U.S. Patent # 11651165 contain every limitation of the claims of the present application or the claims of the present application are obvious variants thereof. It should be noted that this is in fact a non-provisional non-statutory obviousness-type double patenting rejection because the conflicting claims have in fact been patented.
As an example; claim 17 of the instant application and claim 1 of U.S. Patent # 11651165 both contain a method, comprising receiving, at a processor, a graph data structure that includes a first node associated with a first compute device from a plurality of compute devices, a second node associated with a second compute device from the plurality of compute devices, and an edge between the first node and the second node and having an edge weight that represents a state; determining, via the processor and based on the edge weight, a collective state associated with a user of the first compute device and a user of the second compute device; providing, via the processor, an indication of the collective state as input to an intervention model to determine an intervention and modifying, via the processor, the intervention model based on historical data that includes an indication of the intervention. One of ordinary skill in the art would recognize that it would have been obvious at the time of the invention to drop narrower limitations in order to have a patent with wider applicability and freedom to operate. In other words, the narrower claim 1 of U.S. Patent # 11651165 anticipate the broader claim 17 of the instant application. Also, removal of the additional steps is obvious: In re Karlson, 136 USPQ 184 (1963): "Omission of an element and its function is an obvious expedient if the remaining elements perform the same functions as before".
Claim 17-36 of the instant Application are also rejected on the ground of non-statutory obviousness-type double patenting as being unpatentable over claims 1-19 of U.S. Patent # 10860805. Although the conflicting claims are not identical, they are not patentably distinct from each other because the claims of the present application are broader in scope than those of U.S. Patent # 10860805 and hence the claims of U.S. Patent # 10860805 can anticipate those of the present invention. That is, the claims of U.S. Patent # 10860805 contain every limitation of the claims of the present application or the claims of the present application are obvious variants thereof. It should be noted that this is in fact a non-provisional non-statutory obviousness-type double patenting rejection because the conflicting claims have in fact been patented.
As an example; claim 17 of the instant application and claim 1 of U.S. Patent # 10860805 both contain a method, comprising receiving, at a processor, a graph data structure that includes a first node associated with a first compute device from a plurality of compute devices, a second node associated with a second compute device from the plurality of compute devices, and an edge between the first node and the second node and having an edge weight that represents a state; determining, via the processor and based on the edge weight, a collective state associated with a user of the first compute device and a user of the second compute device; providing, via the processor, an indication of the collective state as input to an intervention model to determine an intervention and modifying, via the processor, the intervention model based on historical data that includes an indication of the intervention. One of ordinary skill in the art would recognize that it would have been obvious at the time of the invention to drop narrower limitations in order to have a patent with wider applicability and freedom to operate. In other words, the narrower claim 1 of U.S. Patent # 11651165 anticipate the broader claim 17 of the instant application. Also, removal of the additional steps is obvious: In re Karlson, 136 USPQ 184 (1963): "Omission of an element and its function is an obvious expedient if the remaining elements perform the same functions as before".
Claim 17-36 of the instant Application are also rejected on the ground of non-statutory obviousness-type double patenting as being unpatentable over claims 1-19 of U.S. Patent # 12265793. Although the conflicting claims are not identical, they are not patentably distinct from each other because the claims of the present application are broader in scope than those of U.S. Patent # 12265793 and hence the claims of U.S. Patent # 12265793 can anticipate those of the present invention. That is, the claims of U.S. Patent # 12265793 contain every limitation of the claims of the present application or the claims of the present application are obvious variants thereof. It should be noted that this is in fact a non-provisional non-statutory obviousness-type double patenting rejection because the conflicting claims have in fact been patented.
As an example; claim 17 of the instant application and claim 1 of U.S. Patent # 12265793 both contain a method, comprising receiving, at a processor, a graph data structure that includes a first node associated with a first compute device from a plurality of compute devices, a second node associated with a second compute device from the plurality of compute devices, and an edge between the first node and the second node and having an edge weight that represents a state; determining, via the processor and based on the edge weight, a collective state associated with a user of the first compute device and a user of the second compute device; providing, via the processor, an indication of the collective state as input to an intervention model to determine an intervention and modifying, via the processor, the intervention model based on historical data that includes an indication of the intervention. One of ordinary skill in the art would recognize that it would have been obvious at the time of the invention to drop narrower limitations in order to have a patent with wider applicability and freedom to operate. In other words, the narrower claim 1 of U.S. Patent # 12265793 anticipate the broader claim 17 of the instant application. Also, removal of the additional steps is obvious: In re Karlson, 136 USPQ 184 (1963): "Omission of an element and its function is an obvious expedient if the remaining elements perform the same functions as before".
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
6. Claims 17-18, 20-21, 23 and 31 are rejected under 35 U.S.C. 102 (a) (2) as being anticipated by Cha (U.S. Patent Application Publication # 2018/0165582 A1).
With regards to claim 17, Cha teaches a method, comprising receiving, at a processor, a graph data structure that includes a first node associated with a first compute device from a plurality of compute devices, a second node associated with a second compute device from the plurality of compute devices, and an edge between the first node and the second node and having an edge weight that represents a state (Para 63, teaches a social network represented by a graph, i.e., a data structure including edges and nodes. Para 64, teaches that if users in the social networking system are represented as nodes in the social graph, the term “friend” can refer to an edge formed between and directly connecting two user nodes. Para 67, teaches that the social networking system generates and maintains the “social graph” comprising a plurality of nodes interconnected by a plurality of edges. The edges between nodes can be weighted. The weight of an edge can represent an attribute associated with the edge, such as a strength of the connection or association between nodes);
determining, via the processor and based on the edge weight, a collective state associated with a user of the first compute device and a user of the second compute device (Para 67, teaches that the edges between nodes can be weighted. The weight of an edge can represent an attribute associated with the edge, such as a strength of the connection or association between nodes. Different types of edges can be provided with different weights. For example, an edge created when one user “likes” another user may be given one weight, while an edge created when a user befriends another user may be given a different weight);
providing, via the processor, an indication of the collective state as input to an intervention model to determine an intervention (Para 68, teaches that when a first user identifies a second user as a friend, an edge in the social graph is generated connecting a node representing the first user and a second node representing the second user);
and modifying, via the processor, the intervention model based on historical data that includes an indication of the intervention (Para 68, teaches that as various nodes relate or interact with each other, the social networking system modifies edges connecting the various nodes to reflect the relationships and interactions).
With regards to claim 18, Cha teaches the method of claim 17, wherein the edge is from a plurality of edges having a plurality of edge weights and associated with a plurality of states and the determining the collective state is based on the plurality of edges having the plurality of edge weights (Para 67, teaches that the social networking system generates and maintains the “social graph” comprising a plurality of nodes interconnected by a plurality of edges. The edges between nodes can be weighted. The weight of an edge can represent an attribute associated with the edge, such as a strength of the connection or association between nodes. Different types of edges can be provided with different weights. For example, an edge created when one user “likes” another user may be given one weight, while an edge created when a user befriends another user may be given a different weight).
With regards to claim 20, Cha teaches the method of claim 17, further comprising receiving, at the processor, text data associated with the first compute device and the second compute device (Para 74, teaches that the second user may then send the first user a message within the social networking system);
And providing the text data as input, via the processor, to a machine learning model to determine the edge weight that represents the state (Para 74, further teaches that the action of sending the message, which may be stored, is another edge between the two nodes in the social graph representing the first user and the second user).
With regards to claim 21, Cha teaches the method of claim 17, further comprising providing temporal graph pattern data as input, via the processor, to a machine learning model to select a metric from a plurality of metrics, the collective state being determined based on the metric. (Para 46, teaches a sentiment evaluation module that can determine a sentiment score and a corresponding sentiment label for a conversation in or near real time as the conversation proceeds. The sentiment score and the sentiment label for a conversation can change over time. For example, a conversation can start out positive and become negative over time. Accordingly, the sentiment score and the sentiment label for the conversation can be determined as the conversation proceeds. The sentiment evaluation module can determine a sentiment score and a sentiment label for the conversation based on utterances and information up to a current point in time. In this way, the sentiment evaluation module may classify conversations associated with users according to appropriate sentiment labels).
With regards to claim 23, Cha teaches the method of claim 17, wherein the intervention is associated with an increase in cross-clique communication among the plurality of compute devices (Para 69, teaches that the social networking system also includes user-generated content, which enhances a user's interactions with the social networking system. User-generated content may include anything a user can add, upload, send, or “post” to the social networking system. For example, a user communicates posts to the social networking system from a user device. Posts may include data such as status updates or other textual data, location information, images such as photos, videos, links, music or other similar data and/or media. Content may also be added to the social networking system by a third party. Content “items” are represented as objects in the social networking system. In this way, users of the social networking system are encouraged to communicate with each other by posting text and content items of various types of media through various communication channels. Such communication increases the interaction of users with each other and increases the frequency with which users interact with the social networking system).
With regards to claim 31, Cha teaches a method, comprising receiving, via a processor, a first graph data structure that includes a plurality of nodes associated with a plurality of compute devices, at least one layer that includes at least one node from the plurality of nodes and is associated with at least one attribute, and an edge that is associated with the plurality of compute devices and has an edge weight that represents a state (Para 63, teaches a social network represented by a graph, i.e., a data structure including edges and nodes. Para 64, teaches that if users in the social networking system are represented as nodes in the social graph, the term “friend” can refer to an edge formed between and directly connecting two user nodes. Para 65, teaches bilateral connections and indirect connections via one or more levels of connections or degrees of separation. Para 67, teaches that the social networking system generates and maintains the “social graph” comprising a plurality of nodes interconnected by a plurality of edges. The edges between nodes can be weighted. The weight of an edge can represent an attribute associated with the edge, such as a strength of the connection or association between nodes);
providing, via the processor, temporal graph pattern data as input to a machine learning model to select a metric from a plurality of metrics, the temporal graph pattern data being associated with at least one second graph data structure that is generated before the first graph data structure (Para 46, teaches a sentiment evaluation module that can determine a sentiment score and a corresponding sentiment label for a conversation in or near real time as the conversation proceeds. The sentiment score and the sentiment label for a conversation can change over time. A conversation can start out positive and become negative over time. Accordingly, the sentiment score and the sentiment label for the conversation can be determined as the conversation proceeds. The sentiment evaluation module can determine a sentiment score and a sentiment label for the conversation based on utterances and information up to a current point in time. In this way, the sentiment evaluation module may classify conversations associated with users according to appropriate sentiment labels. Para 63, teaches that the social network can be represented by a graph, i.e., a data structure including edges and nodes. Other data structures can also be used to represent the social network, including but not limited to databases, objects, classes, meta elements, files, or any other data structure);
in response to selecting the metric, determining, via the processor, a value for the metric based on the first graph data structure (Para 47, teaches that Sentiment scores and/or sentiment labels associated with conversations can have various applications. Changes in sentiment scores and/or sentiment labels for conversations can be monitored, and various actions can be taken based on the changes. If a conversation between a user and an agent becomes negative and stays negative for a period of time, an agent that is more experienced can step in for the conversation or provide tips to the agent. Monitoring can include determining whether a rating of a conversation satisfies a threshold value);
determining, via the processor and based on the value, a collective state for a plurality of users associated with the plurality of compute devices (Para 47, further teaches that it can be determined whether a rating of a conversation falls below a threshold rating e.g., “fair” rating. Monitoring can also include determining whether an amount of time associated with a rating of a conversation satisfies a threshold value. It can be determined whether an amount of time associated with a rating of a conversation exceeds a threshold amount of time. The threshold amount of time can be specified in units of time e.g., seconds, minutes, etc. Most recent utterances associated with a rating can be considered. Monitoring can further include determining whether a number of utterances associated with a rating satisfies a threshold value. Instead of or in addition to determining an amount of time associated with a rating of a conversation, it can be determined whether a number of utterances associated with a rating exceeds a threshold number. Most recent utterances associated with a rating can be considered);
and causing, via the processor, transmission of a signal indicating the collective state (Para 47, further teaches that actions to be taken based on monitoring can be specified. Notifications or alerts can be sent to agents or other entities regarding conversations that may require special actions. Agents can be automated agents, and a human agent can step in for a conversation if a special action is required).
Allowable Subject Matter
7. Claims 19, 22, 24-30 and 32-36 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and further if the double patenting rejection is overcome. The prior art of record, alone or in combination, does not currently suggest or teach the invention as outlined in these claims. The Examiner shall outline more detailed reasons for allowance as and when the Application proceeds to allowability.
Conclusion
8. The following prior art, made of record but not relied upon, is considered pertinent to applicant's disclosure: Rapaport (U.S. Patent Application Publication # 2010/0205541 A1), Donohue (U.S. Patent Application Publication # 2017/0147202 A1). These references are also included in the PTO-892 form attached with this office action.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to NEERAJ SHARMA whose contact information is given below. The examiner can normally be reached on Monday to Friday 8 am to 5 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Louis-Desir can be reached on 571-272-7799 (Direct Phone). The fax number for the organization where this application or proceeding is assigned is 571-273-8300.
/NEERAJ SHARMA/
Primary Examiner, Art Unit 2659
571-270-5487 (Direct Phone)
571-270-6487 (Direct Fax)
neeraj.sharma@uspto.gov (Direct Email)
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