DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is a response to an amendment/arguments filed on 4/6/2026 which was in response to the office action mailed on 12/4/2025 (hereinafter the prior office action).
Claim(s) 1-15 is/are pending.
Claim(s) 1, 6-8 and 13-15 is/are amended.
Claim(s) 1, 8 and 15 is/are independent.
Applicant’s amendments have overcome prior rejection(s) based on 35 U.S.C. 112.
Response to Arguments
Applicant’s arguments, filed on 4/6/2026, have been fully considered but they are not persuasive.
Applicant states in Pg. 9 in “Remarks” that the claimed invention addresses both switching to a new product or adding a new product unlike the prior art.
Examiner respectfully disagrees because Choi teaches addressing a new product. This is because Choi discloses in Para. 252 that recognized device is determined to be a new device based on use history; further, Choi discloses in Para. 69, 147, 158 that new device is identified using various information collected from the device, i.e. registration information; further, Choi discloses in Para. 252 that if the new device is the same type as an existing device, existing device information, i.e. history data associated with existing home appliance, is used to create, i.e. convert to, new device information. Thus, Choi deals with adding a new device as Applicant’s invention.
Further, in response to applicant's argument that the references fail to show certain features of applicant’s invention, it is noted that the features upon which applicant relies (i.e., switching to a new product) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant further states in Pg. 10 in “Remarks” that Kwon is limited to recommend course and option through deep learning of use histories of course or option previously input or performed, and that the combination of Choi and Kwon does not teach transferring features between a existing device and a new device including converting cycle history data to a form executable by the home appliance.
Examiner respectfully disagrees because it is Choi, and not Kwon, that teaches converting data in a form executable by the home appliance (Choi, Para. 252), while Kwon teaches the recommendation service (Kwon, Para. 161, etc.) and the cycle data (Kwon, Para. 119, 251). In response to applicant's arguments against the references individually, one cannot show nonobviousness 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). Thus, in this case, it is the combination of Choi and Kwon, and not any individual art, that teaches the claim limitations.
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 of this title, 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 6, 8-9, 13 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Choi et al. (U.S. Pub. No. 2018/0285463) (hereinafter “Choi”) in view of Kwon et al. (U.S. Pub. No. 2018/0305851) (hereinafter “Kwon”).
Regarding claim 1, Choi teaches a method, performed by a server, of providing an artificial intelligence (AI) service, (Fig. 1, Para. 38 - - server is used, where the server can be an artificial intelligence electronic device)
the method comprising:…determining whether the home appliance is a new device, based on device registration information and usage history information of the home appliance; (Para. 252 - - recognized device is determined to be a new device based on use history; Para. 69, 147, 158 - - new device is identified using various information collected from the device, i.e. registration information)
based on the home appliance being determined as the new device and the home appliance being a same type as an existing home appliance, converting existing first…history data associated with the existing home appliance into second…history data in a form executable by the home appliance; (Para. 252 - - if the new device is the same type as an existing device, existing device information, i.e. history data associated with existing home appliance, is used to create, i.e. convert to, new device information)
But Choi does not explicitly teach receiving, from a home appliance, a signal requesting a course recommendation service;
cycle history data
obtaining information associated with a recommended course of the home appliance by applying the second cycle history data as input data to an Al model;
and transmitting, to the home appliance, the information associated with the recommended course of the home appliance as part of the course recommendation service.
However, Kwon teaches receiving, from a home appliance, a signal requesting a course recommendation service; (Para. 161 - - recommendation requesting unit is used)
cycle history data (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
obtaining information associated with a recommended course of the home appliance by applying the second cycle history data as input data to an Al model; (Para. 130 - - data is applied to a machine learning or deep learning, i.e. AI, model)
and transmitting, to the home appliance, the information associated with the recommended course of the home appliance as part of the course recommendation service. (Para. 140, 161 - - recommendation is transmitted)
Choi and Kwon are analogous art because they are from the same field of endeavor and contain overlapping structural and/or functional similarities. They both contain home electronic devices that are controlled based on obtained data.
Therefore, before the effective filing date of the claimed invention (AIA ), it would have been obvious to a person of ordinary skill in the art to modify the above limitation(s) as taught by Choi, by incorporating the above limitation(s) as taught by Kwon.
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 2, Choi further teaches wherein the converting of the first…history data into the second…history data is based on a preset course mapping relationship between courses of the existing home appliance and courses of the home appliance. (Para. 252 - - existing capability information is used as a source for the creation, i.e. mapping, for new device)
Kwon further teaches cycle history data (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 6, Choi further teaches obtaining a mapping relationship between first…information according to a course executable by the existing home appliance and second…information according to a course executable by the home appliance, (Para. 252 - - existing capability information is used as a source for the creation, i.e. mapping using first information, for new device, i.e. second information)
based on a similarity between the first…information and the second…information; (Para. 252 - - existing capability information, i.e. first information, is similar to second information which is created based on first information)
and converting the first…information into the second…information, based on the obtained mapping relationship. (Para. 252 - - existing device information, i.e. first course, is used to create, i.e. convert to, second course)
Kwon further teaches cycle history data…cycle information…cycle history information (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 8, Choi teaches a server for providing an artificial intelligence (Al) service to a home appliance, (Fig. 1, Para. 38 - - server is used, where the server can be an artificial intelligence electronic device)
the server comprising: a communication interface; a memory to store…history data of at least one home appliance and at least one instruction; and at least one processor configured to execute the at least one instruction stored in the memory (Fig. 1, Para. 340 - - computer with communication interface, memory and processor is used)
to:…determine whether the home appliance is a new device, based on device registration information and usage history information of the home appliance, (Para. 252 - - recognized device is determined to be a new device based on use history; Para. 69, 147, 158 - - new device is identified using various information collected from the device, i.e. registration information)
based on the home appliance being determined as the new device and the home appliance being a same type as an existing home appliance, convert, before use of the home appliance, existing first…history data associated with the existing home appliance into second…history data in a form executable by the home appliance, (Para. 252 - - if the new device is the same type as an existing device, existing device information, i.e. history data associated with existing home appliance, is used to create, i.e. convert to, new device information)
But Choi does not explicitly teach receive a signal requesting a course recommendation service from the home appliance through the communication interface,
cycle history data
obtain information associated with a recommended course of the home appliance by applying the second cycle history data as input data to a first Al model,
and control the communication interface to transmit, to the home appliance, the information associated with the recommended course of the home appliance as part of the course recommendation service.
However, Kwon teaches receive a signal requesting a course recommendation service from the home appliance through the communication interface, (Para. 161 - - recommendation requesting unit is used)
cycle history data (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
obtain information associated with a recommended course of the home appliance by applying the second cycle history data as input data to a first Al model, (Para. 130 - - data is applied to a machine learning or deep learning, i.e. AI, model)
and control the communication interface to transmit, to the home appliance, the information associated with the recommended course of the home appliance as part of the course recommendation service. (Para. 140, 161 - - recommendation is transmitted)
Choi and Kwon are analogous art because they are from the same field of endeavor and contain overlapping structural and/or functional similarities. They both contain home electronic devices that are controlled based on obtained data.
Therefore, before the effective filing date of the claimed invention (AIA ), it would have been obvious to a person of ordinary skill in the art to modify the above limitation(s) as taught by Choi, by incorporating the above limitation(s) as taught by Kwon.
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 9, Choi further teaches to convert the first…history data into the second…history data, based on a preset course mapping relationship between courses of the existing home appliance and courses of the new home appliance. (Para. 252 - - existing capability information is used as a source for the creation, i.e. mapping, for new device)
Kwon further teaches cycle history data (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 13, Choi further teaches to: obtain a mapping relationship between first…information according to the course executable by the existing home appliance and second…information according to the course executable by the home appliance, (Para. 252 - - existing capability information is used as a source for the creation, i.e. mapping using first information, for new device, i.e. second information)
based on a similarity between the first…information and the second…information; (Para. 252 - - existing capability information, i.e. first information, is similar to second information which is created based on first information)
and convert the first…information into the second…information, based on the obtained mapping relationship. (Para. 252 - - existing device information, i.e. first course, is used to create, i.e. convert to, second course)
Kwon further teaches cycle history data…cycle information…cycle history information (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Regarding claim 15, Choi teaches a computer program product including a non-transitory computer-readable storage medium storing instructions executable by a server to cause the server to execute an operation (Fig. 1, Para. 340 - - computer with communication interface, memory and processor is used)
comprising:…determining whether the home appliance is a new device, based on device registration information and usage history information of the home appliance; (Para. 252 - - recognized device is determined to be a new device based on use history; Para. 69, 147, 158 - - new device is identified using various information collected from the device, i.e. registration information)
converting, before used of the home appliance, based on the appliance being determined as the new device and the home appliance being a same type as an existing home appliance, existing first…history data associated with the existing home appliance into second…history data in a form executable by the home appliance; (Para. 252 - - if the new device is the same type as an existing device, existing device information, i.e. history data associated with existing home appliance, is used to create, i.e. convert to, new device information)
But Choi does not explicitly teach receiving, from a home appliance, a signal requesting a course recommendation service;
cycle history data
obtaining information associated with a recommended course by applying the second cycle history data as input data to a first artificial intelligence (Al) model;
and transmitting, to the home appliance, the information associated with the recommended course as part of the course recommendation service.
However, Kwon teaches receiving, from a home appliance, a signal requesting a course recommendation service; (Para. 161 - - recommendation requesting unit is used)
cycle history data (Para. 251 - - historical data is used for laundry apparatus; Para. 119 - - where laundry apparatus is a cycle device)
obtaining information associated with a recommended course by applying the second cycle history data as input data to a first artificial intelligence (Al) model; (Para. 130 - - data is applied to a machine learning or deep learning, i.e. AI, model)
and transmitting, to the home appliance, the information associated with the recommended course as part of the course recommendation service. (Para. 140, 161 - - recommendation is transmitted)
Choi and Kwon are analogous art because they are from the same field of endeavor and contain overlapping structural and/or functional similarities. They both contain home electronic devices that are controlled based on obtained data.
Therefore, before the effective filing date of the claimed invention (AIA ), it would have been obvious to a person of ordinary skill in the art to modify the above limitation(s) as taught by Choi, by incorporating the above limitation(s) as taught by Kwon.
One of ordinary skill in the art would have been motivated to do this modification in order to compute and recommend a course and option for a home apparatus, as suggested by Kwon (Para. 23, 127).
Allowable Subject Matter
Claim(s) 3-5, 7, 10-12 and 14 is/are objected to as being dependent upon a rejected base claim(s), but would be allowable if rewritten in independent form including all of the limitations of the base claim(s) and any intervening claim(s).
The following is an examiner’s statement of reasons for allowance:
While Choi et al. (U.S. Pub. No. 2018/0285463) discloses generating user profile including acquiring information corresponding to external devices and generating or updating a user profile corresponding to a user of the device,
and while Kwon et al. (U.S. Pub. No. 2018/0305851) discloses controlling a laundry treating apparatus including a recommendation request unit to recommend a laundry treating course,
none of these references taken either alone or in combination with the prior art of record disclose, in combination with the remaining elements and features of the claimed invention, a server providing an artificial intelligence (AI) service to a home appliance including:
Claim 3 (including limitations of base claim 1),
receiving, from a home appliance, a signal requesting a course recommendation service;
determining whether the home appliance is a new device, based on device registration information and usage history information of the home appliance;
when the home appliance is determined as the new device, converting existing first cycle history data associated with an existing home appliance before use of the home appliance and that is a same type as the home appliance into second cycle history data corresponding to the home appliance;
obtaining information associated with a recommended course of the home appliance by applying the second cycle history data as input data to an Al model; and
transmitting, to the home appliance, the information associated with the recommended course of the home appliance.
wherein the Al model is a first Al model and the converting of the first cycle history data into the second cycle history data comprises:
extracting at least one feature value from the first cycle history data;
performing inference through a second Al model by applying the extracted at least one feature value as input data to the second Al model; and
converting the first cycle history data into the second cycle history data, based on a label obtained through the inference.
Claim 7 (including limitations of base claim 1),
receiving, from a home appliance, a signal requesting a course recommendation service;
determining whether the home appliance is a new device, based on device registration information and usage history information of the home appliance;
when the home appliance is determined as the new device, converting existing first cycle history data associated with an existing home appliance before use of the home appliance and that is a same type as the home appliance into second cycle history data corresponding to the home appliance;
obtaining information associated with a recommended course of the home appliance by applying the second cycle history data as input data to an Al model; and
transmitting, to the home appliance, the information associated with the recommended course of the home appliance.
wherein the obtaining of the information associated with the recommended course of the home appliance comprises:
obtaining, from the home appliance, use environment information comprising information associated with at least one of a usage time, a usage date, a day of the week, an external temperature, humidity, or fine dust; extracting a feature value from the use environment information;
generating a feature vector by using the extracted feature value and a feature value extracted from the second cycle history data; and
obtaining a label representing the recommended course of the home appliance, by applying the feature vector as input data to the Al model and performing inference through the Al model.
Claim 10 (including limitations of base claim 8),
receive a signal requesting a course recommendation service from the home appliance through the communication interface,
determine whether the home appliance is a new device, based on device registration information and usage history information of the home appliance,
when the home appliance is determined as the new device, convert existing first cycle history data associated with an existing home appliance before use of the home appliance and that is a same type as the home appliance into second cycle history data corresponding to the home appliance, obtain information associated with a recommended course of the home appliance by applying the second cycle history data as input data to a first Al model, and
control the communication interface to transmit, to the home appliance, the information associated with the recommended course of the home appliance.
extract at least one feature value from the first cycle history data;
perform inference through a second Al model by applying the extracted at least one feature value as input data to the second Al model; and
convert the first cycle history data into the second cycle history data, based on a label obtained through the inference.
Claim 14 (including limitations of base claim 8),
receive a signal requesting a course recommendation service from the home appliance through the communication interface,
determine whether the home appliance is a new device, based on device registration information and usage history information of the home appliance,
when the home appliance is determined as the new device, convert existing first cycle history data associated with an existing home appliance before use of the home appliance and that is a same type as the home appliance into second cycle history data corresponding to the home appliance, obtain information associated with a recommended course of the home appliance by applying the second cycle history data as input data to a first Al model, and
control the communication interface to transmit, to the home appliance, the information associated with the recommended course of the home appliance.
obtain use environment information comprising information associated with at least one of a usage time, a usage date, a day of the week, an external temperature, humidity, or fine dust, from the home appliance through the communication interface; and
extract a feature vector from the use environment information, generate a feature vector by using the extracted feature value and a feature value extracted from the second cycle history data, and obtain a label representing the recommended course of the home appliance, by applying the feature vector as input data to the first Al model and performing inference through the first Al model.
It is for these reasons that the applicant’s invention defines over the prior art of record.
Claims 4, 5, 11 and 12, being definite, further limiting, and fully enabled by the specification, depend on the above allowed independent claim(s), and thus would also be allowed if at least their base claims 3 and 10 were rewritten as outlined above.
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference 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. See MPEP 2123.
Citation of Pertinent Prior Art
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Pub. No. 2021/0156068 by Kim et al., which discloses artificial intelligence used to determine whether an option in a course is changed when user input is received and collecting use history information (Title/Abstract).
Conclusion
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 extension fee 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Saad M. Kabir whose telephone number is 571-270-0608 (direct fax number is 571-270-9933). The examiner can normally be reached on Mondays to Fridays 9am to 5pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mohammad Ali can be reached on 571-272-4105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SAAD M KABIR/
Examiner, Art Unit 2119
/MOHAMMAD ALI/Supervisory Patent Examiner, Art Unit 2119
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