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
This action is responsive to the Application filed on 11/30/2023. Claims 1-20 are pending in the case. Claims 1, 12 and 18 are independent claims.
Claim Objections
Claims 7 and 17 are objected to because of the following informalities: “a language model” should be “the language model”. Appropriate correction is required.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over
Siebel et al (US 20220405775 A1) in view of McDonnell et al (US 20130218991 A1).
Referring to claims 1, 12 and 18, McDonnell discloses a system comprising: a processor; and a computer-readable medium storing instructions that are operative upon execution by the processor to:
receive a trigger to generate an outgoing message as a response to an incoming message from a message source; ([0052] of McDonnell, “the record handler component 312 can be configured to provide the record identifier(s) 331 of the accessible record(s) 315 to the outgoing data handler component 309 in the CRM system 300. The outgoing data handler 309 can be configured to build a message that includes at least one record identifier 331 of at least one accessible record 315, and to interoperate directly with the protocol layer of the network subsystem 302 or with an application protocol layer 303. The message including the record identifier(s) 331 can be transmitted as a whole or in parts via the network subsystem 302 over the network 230 to the requesting user system 400 associated with the user 203.”)
extract features from the incoming message; ([0045] of McDonnell, record handler component 312 can be configured to extract the user-specific information 471 and/or the enterprise-specific information 481 from the message and to generate at least one search query for CRM records 320 relating to the user-specific 471 and/or the enterprise-specific 481 information)
identify a plurality of data records associated with the message source, the plurality of data records located within a data set; ([0095] of McDonnell, “the relevancy score handler component 316 can be configured to select at least one recommended record 318 from the accessible records 315 by generating a sorted list comprising the accessible records 315 sorted by their respective relevance scores 332, 342. In an embodiment, the accessible records 315 can be sorted in an order from highest score 332, 342 to lowest score 332, 342, i.e., most relevant to least relevant. Once the sorted list is generated, the relevancy score handler component 316 can be configured to select a predetermined number of accessible records 315 from the sorted list, e.g., the top five (5) records, to be the at least one recommended record 318. In an embodiment, the predetermined number can be a default value set by the administrator or a value defined by the user 203 and stored as a user preference 333 with the user information 330.”)
identify, in each data record of the plurality of data records, data record features; ([0095] of McDonnell, “the relevancy score handler component 316 can be configured to select at least one recommended record 318 from the accessible records 315 by generating a sorted list comprising the accessible records 315 sorted by their respective relevance scores 332, 342. In an embodiment, the accessible records 315 can be sorted in an order from highest score 332, 342 to lowest score 332, 342, i.e., most relevant to least relevant. Once the sorted list is generated, the relevancy score handler component 316 can be configured to select a predetermined number of accessible records 315 from the sorted list, e.g., the top five (5) records, to be the at least one recommended record 318. In an embodiment, the predetermined number can be a default value set by the administrator or a value defined by the user 203 and stored as a user preference 333 with the user information 330.”)
rank a set of data records of the plurality of data records using a ML model, based on at least a similarity of features extracted from the incoming message with data record features in each data record of the set of data records; ([0095] of McDonnell, “the relevancy score handler component 316 can be configured to select at least one recommended record 318 from the accessible records 315 by generating a sorted list comprising the accessible records 315 sorted by their respective relevance scores 332, 342. In an embodiment, the accessible records 315 can be sorted in an order from highest score 332, 342 to lowest score 332, 342, i.e., most relevant to least relevant. Once the sorted list is generated, the relevancy score handler component 316 can be configured to select a predetermined number of accessible records 315 from the sorted list, e.g., the top five (5) records, to be the at least one recommended record 318. In an embodiment, the predetermined number can be a default value set by the administrator or a value defined by the user 203 and stored as a user preference 333 with the user information 330.” Here, ranking which data records to use based on the ranked relevance/similarity score where relevance is [0055] of McDonnell, “ For example, when the record 315 under consideration is a contact record 322 corresponding to a person, e.g., the user's contact 201a, a relevance factor 317 can be directed to a frequency with which the user 203 has interactions with the contact 201a associated with the contact record 322, i.e., how many times has the user 203 called, emailed, and/or texted the contact 201a.” Even though McDonnell does not specifically disclose a “ML model”, but neither the claim nor the Specification explained how this ML model is used to train anything, hence under BRI, it is interpreted as a software model)
present the set of data records in a user interface (UI), indicating the ranking; ([0187] of McDonnell, “A UI 730 provides a user interface and an API 732 provides an application programmer interface to system 616 resident processes to users and/or developers at user systems 612.”)
receive a selection from the UI, the selection indicating a selected data record of the set of data records; ([0092] of McDonnell, “Referring again to FIG. 1A, once the relevance score(s) 332, 342 for each of the accessible records 315 is determined, at least one recommended record is selected from the plurality of accessible records 315, in block 108, based on the relevance score 332, 342 of the recommended record(s). According to an embodiment, the relevancy score handler component 316 in the CRM recommendation service 310 can be configured to select at least one recommended record 318 from the plurality of accessible records 315 based on the relevance score 332, 342 of the at least one recommended record 318.”)
dynamically generate, using a language model, the outgoing message using the selected data record; ([0125] of McDonnell, “Once the message 462, 462a is built, the information handler component 460 can be configured, in an embodiment, to provide the message 462, 462a to the outgoing data handler 408 in the user system 400. In an embodiment, the outgoing data handler 408 can be configured to interoperate directly with a protocol layer of a network subsystem 404 or with an application protocol layer 406. The message 462, 462a including the request and user-specific information 471 and/or enterprise-specific information 481 can be transmitted as a whole or in parts via the network subsystem 404 over the network 230 to the CRM server 220 hosting CRM system 300.”) and
transmit the outgoing message across a network to the message source. ([0125] of McDonnell, “Once the message 462, 462a is built, the information handler component 460 can be configured, in an embodiment, to provide the message 462, 462a to the outgoing data handler 408 in the user system 400. In an embodiment, the outgoing data handler 408 can be configured to interoperate directly with a protocol layer of a network subsystem 404 or with an application protocol layer 406. The message 462, 462a including the request and user-specific information 471 and/or enterprise-specific information 481 can be transmitted as a whole or in parts via the network subsystem 404 over the network 230 to the CRM server 220 hosting CRM system 300.”)
Referring to claims 2, 13 and 19, McDonnell discloses the system of claim 1, wherein the instructions are further operative to:
prior to presenting the set of data records in the UI, dynamically generate, using the language model, a candidate message using a top-ranked data record of the set of data records;
wherein presenting the set of data records in the UI comprises presenting the set of data records along with presenting the candidate message in the UI; and wherein the selected data record is not the top-ranked data record of the set of data records. ([0121] of McDonnell, generate and select message included a request for recommended records and [0122] of McDonnell)
Referring to claims 3, 14 and 20, McDonnell discloses the system of claim 1, wherein dynamically generating the outgoing message occurs prior to presenting the set of data records in the UI, and the selected data record comprises a top-ranked data record of the set of data records. ([0098] of McDonnell, “once the at least one recommended record 318 is selected, a response message including information identifying the at least one recommended record 318 is transmitted to the requesting user system 400 associated with the user 203. According to an embodiment, a list handler component 319 in the CRM recommendation service 310 is configured to transmit a first response message 334 including information identifying the at least one recommended record 318 to the requesting user system 400.”)
Referring to claim 4, McDonnell discloses the system of claim 1, wherein dynamically generating the outgoing message comprises generating the candidate outgoing message; presenting the candidate outgoing message in the UI, and receiving a user selection of the candidate outgoing message at the UI. ([0098] of McDonnell, “once the at least one recommended record 318 is selected, a response message including information identifying the at least one recommended record 318 is transmitted to the requesting user system 400 associated with the user 203. According to an embodiment, a list handler component 319 in the CRM recommendation service 310 is configured to transmit a first response message 334 including information identifying the at least one recommended record 318 to the requesting user system 400.”)
Referring to claim 5, McDonnell discloses the system of claim 1, wherein the data record features include at least two features selected from the list consisting of: a title of the data record, a contact name, an opportunity owner identified in the data record, an item, and a time of the data record. ([0045] of McDonnell, record handler component 312 can be configured to extract the user-specific information 471 and/or the enterprise-specific information 481 from the message and to generate at least one search query for CRM records 320 relating to the user-specific 471 and/or the enterprise-specific 481 information). Even though McDonnell might not specifically disclose the features disclosed in the claim, but a person of ordinary skills in the art would have understood that modify what “features” to detect is set by the system to detect, hence McDonnell’s “features” can be the features disclosed in the claim with great expectations of success/same result)
Referring to claims 6 and 16, McDonnell discloses the system of claim 1, wherein the features extracted from the incoming message include at least two features selected from the list consisting of: sender name, recipient name, an item mentioned within a title of the incoming message, an item mentioned within a body of the incoming message, and a time of the incoming message. ([0045] of McDonnell, record handler component 312 can be configured to extract the user-specific information 471 and/or the enterprise-specific information 481 from the message and to generate at least one search query for CRM records 320 relating to the user-specific 471 and/or the enterprise-specific 481 information). Even though McDonnell might not specifically disclose the features disclosed in the claim, but a person of ordinary skills in the art would have understood that modify what “features” to detect is set by the system to detect, hence McDonnell’s “features” can be the features disclosed in the claim with great expectations of success/same result)
Referring to claims 7 and 17, McDonnell discloses the system of claim 1, wherein generating the outgoing message comprises generating a language model prompt using the selected data record. Even though McDonnell does not specifically disclose a “language model”, but neither the claim nor the Specification explained how this language model is used to train anything, hence under BRI, it is interpreted as a software model)
Referring to claim 8, McDonnell discloses the system of claim 1, wherein dynamically generating the outgoing message comprises generating a plurality of candidate messages, presenting the plurality of candidate messages in the UI, receiving a user selection of one of the candidate message at the UI, and in response to the user selection, using the selected one of the candidate messages as the outgoing message. ([0098] of McDonnell, “once the at least one recommended record 318 is selected, a response message including information identifying the at least one recommended record 318 is transmitted to the requesting user system 400 associated with the user 203. According to an embodiment, a list handler component 319 in the CRM recommendation service 310 is configured to transmit a first response message 334 including information identifying the at least one recommended record 318 to the requesting user system 400.”)
Referring to claim 9, McDonnell discloses the system of claim 1 wherein transmitting the outgoing message automatically updates the data set. ([0033] and [0150] of McDonnell)
Referring to claim 10, McDonnell discloses the system of claim 9 wherein the selected data record is automatically added to training data used to refine the ML model responsive to receiving the selection indicating the selected data record. ([0033] and [0150] of McDonnell, once the dataset is updated the information is within the system to be used for training)
Referring to claim 11, McDonnell discloses the system of claim 1 wherein dynamically generating the outgoing message comprises generating a plurality of candidate messages, one per data record in the set of ranked data records, and presenting the plurality of candidate messages in the UI one at a time, according to which of the ranked data records is currently selected by a user. ([0099]-[0102] of McDonnell)
Referring to claim 15, McDonnell discloses the computer-implemented method of claim 12, wherein the similarity of features is computed using a machine learning model. Even though McDonnell does not specifically disclose a “machine learning model”, but neither the claim nor the Specification explained how this machine learning model is used to train anything, hence under BRI, it is interpreted as a software model)
Referring to claim 17, McDonnell discloses the computer-implemented method of claim 12, wherein generating the outgoing message comprises generating a language model prompt using the selected data record. ([0098] of McDonnell, “once the at least one recommended record 318 is selected, a response message including information identifying the at least one recommended record 318 is transmitted to the requesting user system 400 associated with the user 203. According to an embodiment, a list handler component 319 in the CRM recommendation service 310 is configured to transmit a first response message 334 including information identifying the at least one recommended record 318 to the requesting user system 400.”)
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Wu (CN 109313650 A): generating a response in a auto-chatting method and device. can be obtained in the chat stream message. it can confirm several candidate in response to the message. can be at least based on knowledge data for ordering the candidate response. can be at least for generating responses to messages based on candidate response of the one or more ordered.
Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
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Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAIMEI JIANG whose telephone number is (571)270-1590. The examiner can normally be reached M-F 9-5pm.
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/HAIMEI JIANG/Primary Examiner, Art Unit 2142
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