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 .
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Response to Amendment
This is in response to Applicant’s amendment which was filed on 10/18/2025 and has been entered. Claims 1 and 10 have been amended. Claim 7 has have been cancelled. No claims have been added. Claims 1-6 and 8-10 are pending in this application, with claims 1 and 10 being independent.
Claim Rejections - 35 USC § 103
Claims 1 – 6 and 8 - 10 are rejected under 35 U.S.C. 103 as being unpatentable over Gruber et al (US 9953088 B2) -hereinafter “Gruber” in view of Brown (US 20150154956 A1)
Gruber discloses a digital assistance server 106 which utilizes natural language processing capabilities so that user requests that are very similar to one another can benefit from the same answers (PP 118, 119).
Regarding Claim 1, Gruber discloses a computer-implemented method for providing an identical response to a similar issue that is received from different customers (“Many of these user requests may be very similar and the same queries and answers may provide the necessary information to resolve all of these user requests, PP 119) via inbound-interaction in a digital multi-channel contact center (“digital assistant server” 106 and “external services” 118, Fig. 1 or in Fig. 3 ), said computer-implemented method comprising:
for each inbound-interaction from a customer (“user request”) that is entering an interactions-queue (see “pool”, PP 122) ,
creating a temporary-case for an issue raised in the inbound-interaction (see PP 122, establishing a special query pool for handling queries that are each relevant to the fulfillment of multiple similar or equivalent user requests)
operating a Similarity Detection Module (SDM) on the created temporary-case and one or more cases in a cases-queue to receive a similarity-score for the created temporary-case; (PP 118, the query generation module identifies user requests that are very similar to one another and can benefit from the answers to the same queries)
when the received similarity-score is above a second preconfigured threshold (PP 120, the information crowd sourcing module recognizes the commonalities among different user requests. The commonality between two user requests can be found based on a large overlap between the domains and properties activated by the two user requests, also see “sufficiently similar” in PP123, and “equivalent requests” PP 127 ). This obviously indicates a certain “threshold” for deciding that requests have a “large overlap”, “very similar” or “equivalent”). Also, see PP 159, based on the respective vocabulary associated with each node in the crowd-sourced knowledge ontology, a new user request will trigger or activate many of the property nodes associated with an existing user request in the crowd-sourced knowledge base, and be identified as similar to the existing user request. Thus having a threshold of similarity would have been obvious in Gruber. That is, for example, 70% match (overlap) between the activated property nodes may be sufficient to consider the two requests as being “similar”.
operating a category Qualifier Module (CQM) on the temporary-case to provide an indication as to qualification of category of the issue raised (read on meeting or exceeding the threshold);
when the provided indication as to qualification of the category of the issued raised is qualified, merging the temporary-case with one or more cases in the cases-queue (special query pool, PP 122) and retrieving a response of the one or more cases m the cases-queue;
sending the retrieved response to the customer (see for example, same answer in PP 118, 119, and see for example PP 132 which states notifying the user that “many users have been experiencing the same issue or have the same question”, and assures the user that a solution or answer should be arriving soon.)
Gruber discusses grouping similar requests and it also discusses sending requests to an external service (Fig. 3B) such as an agent for assistance. See “external services” 118, Fig. 1 or "external services" in Fig. 3 which are used to answer a communication from a user for task completion. PP 168 states that the external services use the questions and answers ("responses") stored in the crowd-sourced knowledge base 358. By using the “pool” as suggested by Gruber or the tag as suggested by Brown, (see below), the related cases will be sent to the same agent/ external resource.
Gruber may differ from the claim in that it does not teach performing the method when that “contact center occupancy rate is above a first preconfigured threshold”. However, Gruber does provide an example (PP 121) wherein a release of a new version of a device operating system may generate many similar issues. This is very similar to the scenario discussed in PP 2, page 1 of applicant’s specification which refers to a “new product”. The teachings of Gruber suggest that some occasions such as the release of a new version of operating system (“new product”) will generate many similar issues which will obviously and expectedly cause the occupancy of the Digital Assistant Server and the external services to be above usual. Using a threshold (such as 70% occupancy) would have been obvious to utilize in Gruber. Note that one of ordinary skill in the art may obviously select to use the techniques taught by Gruber all the time or just during “busy times” when the occupancy is above a predetermined threshold. Note that Gruber teaches that recognizing similarity will make the system “operate more efficiently”. Examiner takes official notice that it extremely well--known in the art that contact/service centers monitor occupancy (“how busy”) and make needed adjustments accordingly.
Gruber does not explicitly teach the similarity score is above a second preconfigured threshold.
However, Brown discloses a very similar system and method for providing an identical response to a similar issue that is received from different customers and explicitly teaches the use of “similarity score”/”threshold” (Brown, PP 0044) being above threshold (see detailed discussion of Brown below). Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to specifically use a threshold so that the “large overlap” as taught by Gruber can be very specific such as 70% as taught by Brown. This offers flexibly for the designer to decide the needed or desired degree of similarity.
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Details of Brown as substantially provided in the previous office action are repeated below:
Brown discloses a computer-implemented method for providing an identical response to a similar issue that is received from different customers (see callers 1-N, 210 Fig. 2 and 611, 613 in Fig. 6) via inbound-interaction in a digital multi-channel contact center (natural language call router 215 in Fig 2 and network 620 in Fig. 6).
For each inbound-interaction from a customer (e.g., a caller #3, item 210, Fig. 2) that is entering an interactions-queue (in PP0015, a natural language call router 215 provides a computer application in which a caller to a customer support call center can speak his/her concerns naturally and in response, the call router then transfers the caller to the appropriate point in the application, or routes them to the appropriate customer representative queue. The claimed step of “creating a temporary-case” reads on creating a tag so that “each of the phrases of words in the predefined set is assigned to or tagged for a particular destination, and a match of the input to such a controlled phase or word causes the router to direct a call to the particular destination (see PP 0002), see also routing to “agent queue” in PP 0002) .
For the claimed “Similarity Detection Module), PP 30 and PP 31 of Brown state that wherein two callers (e.g., caller #3 and caller #77 have the “same issue” / “match”, or “substantially equivalent” issue (e.g., voicemail problem). PP 0044 teaches the degree of matching satisfies a threshold (read as the claimed “second predefined threshold), see also “sufficient degree”.
PP 0015 states that the call router then transfers the caller to the appropriate point in the application, or routes them to the appropriate customer representative queue (read as “assigning …. To an agent”, or takes them to a self-service application routing.
PP0030 teaches merging pair of callers #3 and #77 who have the same issue (e.g., voicemail problem) and tagging them with same tag.
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Thus, Gruber and Brown have many compatible items which makes the combination obvious and one of ordinary skill in the art would be motivated to combine two similar systems which, both handle requests and provide efficiency, accuracy and customer satisfaction.
For Claim 2, “a case” reads on a category/intent as taught by Gruber that requests are categorized based on the speech of the user such as “travel”, “food”, “web browser”, “e-mail”… etc. See for example PP 29 and 31 which teach determining the user’s “intent”. Also, as in the example of releasing a new version of operating system, the Digital Assistance “generates a case” such bas “browser problem”. As discussed above with respect to Claim 1, the techniques may be selectively used if the occupancy is above or below a certain threshold.
Regarding Claim 3, Gruber teaches (PP 60) that user data 348 (Fig. 3B) stores user information such as location (“user address”) and customer details (“such as “user preferences”)
Regarding Claims 4 and 5, Gruber teaches the use of Natural Language Processing module 332, Fig. 3 to determine similarity based on used keywords (uses a sequence of words to determine the intent and then the similarity as discussed above, see PP 48 and 55 and words such as "travel", "car rental"). The determination of a match or no match has been discussed above with respect to claim 1 (see discussion of overlap, equivalent, very similar). No overlap or below the threshold indicate not qualified to be the “same or similar request”.
Regarding Claim 6, PP 137 of Gruber, the information crowd sourcing module optionally searches the crowd-sourced knowledge base (e.g., the crowd-sourced knowledge base 358 in FIGS. 3A-3B and 5 and 7) to see if any of the approved queries for the current user request already exists in the crowd-sourced knowledge base (622). If one or more of the approved queries already exist or have equivalents in the crowd-sourced knowledge base 358, the information crowd sourcing module uses the answers to those queries as the answers for the one or more approved queries.
Regarding Claim 8, the claimed “user” which enters a response reads on an “expert “ in the CS information which provides answers, see PP 121 and 122 of Gruber.
Regarding Claim 9, this reads on the scenario when there is no similarity between a request and existing or previous requests. Obviously, for example, when the new version of operating system is resealed (the example discussed above), a new case (new pool) must be created. This is within the teachings of Gruber.
Claim 10 is rejected for the same reason as discussed above with respect to Claim 1. For example, the claimed “one or more processor” may read on processing modules 114, Fig 1 or 330 in Fig. 3B in Gruber, the claimed memory may read on Data & Models 116 in Fig. 1 or queries pool 520 in Fig. 5 wherein the Crowed Souring Models 342, Fig. 5 create a special query pool.
Response to Arguments
Applicant's arguments filed 10/18/2025 have been fully considered but they are not persuasive.
Applicant argues that “Gruber doesn't teach or suggest system and method for providing an identical response to a similar issue that is received from different customers, via inbound-interaction in a digital multi-channel contact center, as the current application does.”. Examiner respectfully disagrees since Gruber does teach providing an identical response to a similar issue that is received from different customers, as discussed in details above. Applicant argues the references individually.
Applicant also argues that “Brown merely provides a match of identified words with a second data record.”. Examiner respectfully disagrees as Brown teaches much more than that. Brown, as discussed in details in the previous office action and this office action, teaches many of the claimed features such as the use of natural language, tagging g calls that have similar/matching issues such as caller #3 and caller #77, and teaches the use of "degree of matching" and "sufficient degree" of matching.
In response to applicant's arguments against the references individually, one cannot show non-obviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). The combination has a cell center which checks for degree of similarity among incoming calls, tags/pools incoming calls based on the similarity and routes them to the same queue/agent to provide consistent answers.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 116760044 B1 (Mazza) discloses a chatbot (which may be used in a Call Center) has the ability to determine same/duplicate questions based on sematic similarity in order to provide consistent answers, see for example Fig. 5 and Fig. 6.
US 10692006 B1 (Zhang) teaches (PP 35) that when a question is posed to the chatbot system, the chatbot system can first query knowledge base 346 to determine whether that question, or a similar question, is mapped to an answer in the knowledge base 346 for a user with a context that is within a threshold similarity measure to the user currently asking the question.
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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/AHMAD F. MATAR/Supervisory Patent Examiner, Art Unit 2693