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 .
DETAILED ACTION
Claims 1-20 are pending in this office action.
Claim Rejections - 35 USC § 102
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mao et al. (U.S. Patent Pub. No. 2023/0092702).
Regarding claim 1, Mao et al. teaches a system for detection and utilization of end user connection events comprising a computer that includes at least one processor and a memory device storing data and executable code that, when executed, causes the at least one processor to: (a) activate a digital recorder that captures interactive communications and stores the interactive communications to the memory device as an interactive content file (paragraph 0078 and fig. 5, ref. num 502); (b) detect connection event data representing a connection event within the interactive content file and sequence data range designating a beginning and end for the connection event (fig. 5, ref. num 504 and paragraph 0086); (c) generate a connection event subject identification associated with the connection event data (fig. 5, ref. num 508-512); and (d) render a connection event dashboard graphical user interface (“GUI”) displayed on the screen of an agent computer, wherein the connection event dashboard shows a plurality of event subject identifications as a function of sequence data (fig. 5, ref. num 516).
Regarding claim 2, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate an experimental hypothesis using the connection event data that includes (i) operational instructions for implementing the connection event by an agent computer, (ii) conditional data specifying conditions that must be met before the operational instructions are executed; (iii) success criteria that is satisfied or not based on the interactive content data; (b) transmit the experimental hypothesis to the agent computer that generates interactive content data by executing the operational instructions; and (c) compare interactive content data received from the agent computer to determine whether the success criteria is satisfied (paragraph 0037).
Regarding claim 3, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate both (i) operational instructions for implementing the connection event by an agent computer, and (ii) conditional data specifying conditions that must be met before the operational instructions are implemented; and (b) run a chat bot software application that executes the operational instructions when the conditional data is met (paragraph 0076).
Regarding claim 4, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate a training module that comprises (i) operational instructions for implementing a connection event by an agent computer, (ii) conditional data specifying conditions that must be met before the operational instructions are executed, and (iii) training material data; and (b) transmit the training module to an agent computer, wherein the agent computer executes the operational instructions (paragraph 0107).
Regarding claim 5, Mao et al. teaches wherein: (a) the computer comprises a first neural network; and (b) the first neural network is used to detect the connection event data (paragraph 0093).
Regarding claim 6, Mao et al. teaches wherein the first neural network is selected from one of (i) a multilayer perceptron network having three or more layers and that utilizes a nonlinear activation function, (ii) a convolutional neural network; (iii) a recursive neural network, (iv) a recurrent neural network; (v) a Long Short-Term Memory network architecture, or (vi) a Bidirectional Long Short-Term Memory network (paragraph 0093).
Regarding claim 7, Mao et al. teaches wherein: (a) the computer comprises a second neural network; and (b) the second neural network determines the connection event subject identification (paragraph 0090).
Regarding claim 8, Mao et al. teaches wherein the second neural network is selected from one of (i) a Latent Semantic Analysis network, (ii) a Probabilistic Latent Semantic Analysis network, or (iii) a Latent Dirichlet Allocation Network (paragraph 0109).
Regarding claim 9, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) determine sentiment data corresponding to the connection event; and (b) display the sentiment data on the dashboard GUI (paragraph 0078).
Regarding claim 10, Mao et al. teaches wherein: (a) the computer comprises a neural network; (b) the neural network is used to determine the sentiment data; and (c) the neural network is selected from one of (i) a Naive Bayes, Support Vector Machine that uses logical regression, (ii) a convolutional neural network, (iii) a lexical co-occurrence network, or (iv) a Long Short-Term Memory network (paragraph 0093).
Regarding claim 11, Mao et al. teaches a system for detection and utilization of end user connection events comprising a computer that includes at least one processor and a memory device storing data and executable code that, when executed, causes the at least one processor to: (a) activate a digital recorder that captures interactive communications and stores the interactive communications to the memory device as an interactive content file (paragraph 0078 and fig. 5, ref. num 502); (b) detect connection event data representing a connection event within the interactive content file (fig. 5, ref. num 504 and paragraph 0086); (c) generate both (i) operational instructions for implementing the connection event by an agent, and (ii) conditional data specifying conditions that must be met before the operational instructions are implemented (fig. 5, ref. num 516 and paragraph 0129); and (d) transmit the operational instructions and conditional data to an agent computer for execution of the operational instructions when the conditional data is met (fig. 5, ref. num 518).
Regarding claim 12, Mao et al. teaches wherein: (a) the computer comprises a first neural network; and (b) the neural network is used to detect the connection event data (paragraph 0093).
Regarding claim 13, Mao et al. teaches wherein the first neural network is selected from one of (i) a multilayer perceptron network having three or more layers and that utilizes a nonlinear activation function, (ii) a convolutional neural network; (iii) a recursive neural network, (iv) a recurrent neural network; (v) a Long Short-Term Memory network architecture, or (vi) a Bidirectional Long Short-Term Memory network (paragraph 0093).
Regarding claim 14, Mao et al. teaches wherein executing the executable code further causes the processor to render a connection event dashboard graphical user interface (“GUI”) displayed on the screen of an agent computer, wherein the connection event dashboard shows connection events as a function of sequence data (fig. 5, ref. num 516).
Regarding claim 15, Mao et al. teaches wherein the operational instructions and conditional data are integrated with a chat bot software application that executes the operational instructions when the conditional data is met (paragraph 0076).
Regarding claim 16, Mao et al. teaches a system for detection and utilization of end user connection events comprising a computer that includes at least one processor and a memory device storing data and executable code that, when executed, causes the at least one processor to: (a) record connection event data representing a plurality of connection events, sequence data corresponding to each connection event, and a connection event subject identification for each connection event (fig. 5, ref. num 502-512); and (b) render a connection event dashboard graphical user interface (“GUI”) displayed on the screen of an agent computer, wherein the connection event dashboard shows a plurality of event subject identifications as a function of sequence data (fig. 5, ref. num 516).
Regarding claim 17, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate both (i) operational instructions for implementing the connection event by an agent, and (ii) conditional data specifying conditions that must be met before the operational instructions are implemented; and (b) transmit the operational instructions and conditional data to an agent computer for execution of the operational instructions when the conditional data is met (paragraph 0107).
Regarding claim 18, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate both (i) operational instructions for implementing the connection event by an agent, and (ii) conditional data specifying conditions that must be met before the operational instructions are implemented; and (b) integrate the operational instructions and conditional data with a chat bot software application that executes the operational instructions when the conditional data is met (paragraph 0076).
Regarding claim 19, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate an experimental hypothesis using the connection event data that includes (i) operational instructions for executing the connection event by an agent, (ii) conditional data specifying conditions that must be met before the operational instructions are executed; (iii) success criteria that is satisfied or not based on the interactive content data; (b) transmit the experimental hypothesis to an agent computer that generates interactive content data by executing the operational instructions; and (c) compare interactive content data received from the agent computer to determine whether the success criteria is satisfied (paragraph 0037).
Regarding claim 20, Mao et al. teaches wherein executing the executable code further causes the processor to: (a) generate a training module that comprises (i) operational instructions for implementing a connection event by an agent computer, (ii) conditional data specifying conditions that must be met before the operational instructions are executed, and (iii) training material data; and (b) transmit the training module to an agent computer, wherein the agent computer executes the operational instructions (paragraph 0107).
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/BRANDON HOFFMAN/Primary Examiner, Art Unit 2433