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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/24/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because the abstract is too brief to disclose the technical disclosure. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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, 3-7, and 9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jonsson [PGPUB 2011/0294525].
Regarding claim 1, the Jonsson reference discloses a terminal device, comprising a processor and a memory, wherein the memory is configured to store a computer program, and the processor is configured to invoke and run the computer program stored in the memory [ie. user device; Jonsson; figures 1A (110-1) and 3; paragraphs 0038 and 0053-0056], to cause the terminal device to perform:
performing semantic acquisition processing on an information source to obtain semantic information [ie. natural language processing; Jonsson; para 0041, 0043, 0063, and 0079-0080];
determining, based on the semantic information, first information to be transmitted [ie. after classifying to determine information to send; Jonsson; para 0041-0043]; and
sending the first information [ie. output text message; Jonsson; para 0087].
Regarding claim 3, the Jonsson reference further discloses the performing semantic acquisition processing on an information source to obtain semantic information comprises: performing extended semantic acquisition processing on the information source to obtain extended semantic information [ie. mood (“extended semantic information”); “Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para 0041 and 0063-0064].
Regarding claim 4, the Jonsson reference further discloses the performing semantic acquisition processing on an information source to obtain semantic information comprises: performing core semantic acquisition processing on the information source to obtain core semantic information [ie. contextual (“core semantic information”); Jonsson; fig 4; para 0041 and 0065-0066].
Regarding claim 5, the Jonsson reference further discloses the performing semantic acquisition processing on an information source to obtain semantic information comprises: performing extended semantic acquisition processing on the information source to obtain extended semantic information [ie. mood (“extended semantic information”); “Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para oo41 and 0063-0064];
performing core semantic acquisition processing on the information source to obtain core semantic information [ie. contextual (“core semantic information”); Jonsson; fig 4; para 0041 and 0065-0066]; and
obtaining combined semantic information based on the extended semantic information and the core semantic information [ie. both mood and contextual is used (“obtaining combined semantic”) for text messaging; Jonsson; fig 4; para 0042 and 0083].
Regarding claim 6, the Jonsson reference further discloses the performing extended semantic acquisition processing on the information source to obtain extended semantic information comprises at least one of following: inputting the information source into a first trained network model to obtain at least one of emotion information, emphasis information, association information, prediction information, or task priority information; or inputting the information source into a second trained network model to obtain at least one of an emotion information classification, an emphasis information classification, an association information supplement, a prediction information supplement, or a task priority information supplement [The term “or” is used to claim either a first trained network or a second trained network. The Jonsson reference discloses the second trained network. The term “or” is further used within the second trained network claim limitation to claim at least one of an emotion information classification, an emphasis information classification, an association information supplement, a prediction information supplement, or a task priority information supplement”. The Jonsson reference discloses the second trained network for mood classification (“an emotion information classification”); Jonsson; fig 1A; para 0042, 0067, and 0083-0085].
Regarding claim 7, the Jonsson reference further discloses the extended semantic information comprises at least one of emotion information, emphasis information, association information, prediction information, or task priority information [“Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para 0041 and 0063-0064].
Regarding claim 9, the Jonsson reference further discloses the performing core semantic acquisition processing on the information source to obtain core semantic information comprises: inputting the information source into a third trained network model to obtain the core semantic information [ie. using machine learning (natural language component) to obtain contextual information (“core semantic information”); Jonsson; para 0041 and 0063-0066].
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.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Jonsson in view of Chen [PGPUB 2021/0144251].
Regarding claim 2, the Jonsson reference does not specifically disclose “obtaining the first information through encoding and modulating the semantic information; or obtaining the first information through encoding, modulating, and encrypting the semantic information”.
However, in the same field of endeavor, the Chen reference discloses obtaining the first information through encoding and modulating the semantic information; or obtaining the first information through encoding, modulating, and encrypting the semantic information [Chen; fig 14; para 0070 and 0155-0156]. The Jonsson and Chen references are analogous art, since they have similar problem solving area in being able to manage text message communications. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of encoding and modulating information, taught by Chen, into the system, taught by Jonsson. The motivation for doing so would have been to send the messages over a network.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Jonsson in view of Van Dyke et al. (“Van Dyke”) [USPAT 11,170,154].
Regarding claim 8, the Jonsson reference further discloses classifying each piece of information in the extended semantic information [Jonsson; para 0043, 0063, and 0068] but does not specifically disclose “using corresponding identifier information as a classification identifier” and “establishing a mapping relationship based on the classification identifier and a corresponding classification description”.
However, in the same field of endeavor, the Van Dyke reference discloses classifying semantic using corresponding identifier information as a classification identifier and establishing a mapping relationship based on the classification identifier and a corresponding classification description [Van Dyke; fig 5 and 6A; column 4, lines 31-63, col 23, lines 18-63, col 24, lines 25-50, and col 27, lines 53-67]. The Jonsson and Van Dyke references are analogous art, since they have similar problem solving area in being able to manage text message communications. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of classification identifier and mapping, taught by Van Dyke, into the system, taught by Jonsson. The motivation for doing so would have been to easily read the text message.
Claims 10-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Jonsson in view of Jones [USPAT 8,000,729].
Regarding claim 10, the Jonsson reference discloses a terminal device, comprising a processor and a memory, wherein the memory is configured to store a computer program, and the processor is configured to invoke and run the computer program stored in the memory [ie. user device; Jonsson; figures 1A (110-2) and 3; paragraphs 0038 and 0053-0056], to cause the terminal device to perform:
performing semantic acquisition processing on the information source to obtain semantic information [Jonsson; fig 7A and 7B; para 0091-0093].
The Jonsson reference discloses receiving the text message but does not specifically disclose “receiving second information” and “restoring an information source from the second information”.
However, in the same field of endeavor, the Jones reference discloses receiving second information and restoring an information source from the second information [ie. decoding message into text message (“information source”); Jones; abstract; fig 3 and 6; column 2, lines 45-55, col 3, line 49-56, and col 4, lines 35-50]. The Jonsson and Jones references are analogous art, since they have similar problem solving area in being able to manage text message communications. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of decoding, taught by Jones, into the system, taught by Jonsson. The motivation for doing so would have been to be with the standard of Short Message Service and combining prior art elements according to known methods (“encoding/decoding”) to yield predictable results [MPEP 2143].
Regarding claim 11, the combination of Jonsson-Jones further discloses the restoring an information source from the second information comprises at least one of following: obtaining the information source through decoding and demodulating the second information; or obtaining the information source through decoding, demodulating, and decrypting the second information [Jonsson; fig 3; para 0091-0093]. [Jones; abstract; column 3, line 49-56 and col 4, lines 35-50].
Regarding claim 12, the combination of Jonsson-Jones further discloses the performing semantic acquisition processing on the information source to obtain semantic information comprises: performing extended semantic acquisition processing on the information source to obtain extended semantic information [ie. mood (“extended semantic information”); “Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para 0041 and 0063-0064].
Regarding claim 13, the combination of Jonsson-Jones further discloses the performing semantic acquisition processing on the information source to obtain semantic information comprises: performing core semantic acquisition processing on the information source to obtain core semantic information [ie. contextual (“core semantic information”); Jonsson; fig 4; para 0041 and 0065-0066].
Regarding claim 14, the combination of Jonsson-Jones further discloses the performing semantic acquisition processing on the information source to obtain semantic information comprises: performing extended semantic acquisition processing on the information source to obtain extended semantic information [ie. mood (“extended semantic information”); “Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para 0041 and 0063-0064];
performing core semantic acquisition processing on the information source to obtain core semantic information [ie. contextual (“core semantic information”); Jonsson; fig 4; para 0041 and 0065-0066]; and
obtaining combined semantic information based on the extended semantic information and the core semantic information [ie. both mood and contextual is used (“obtaining combined semantic”) for text messaging; Jonsson; fig 4; para 0042 and 0083].
Regarding claim 15, the combination of Jonsson-Jones further discloses the performing extended semantic acquisition processing on the information source to obtain extended semantic information comprises at least one of following: inputting the information source into a fourth trained network model to obtain at least one of emotion information, emphasis information, association information, prediction information, or task priority information; or inputting the information source into a fifth trained network model to obtain at least one of an emotion information classification, an emphasis information classification, an association information supplement, a prediction information supplement, or a task priority information supplement [The term “or” is used to claim either a first trained network or a second trained network. The Jonsson reference discloses the second trained network. The term “or” is further used within the second trained network claim limitation to claim at least one of an emotion information classification, an emphasis information classification, an association information supplement, a prediction information supplement, or a task priority information supplement”. The Jonsson reference discloses the second trained network for mood classification (“an emotion information classification”); Jonsson; fig 1A; para 0042, 0067, and 0083-0085].
Regarding claim 16, the combination of Jonsson-Jones further discloses the extended semantic information comprises at least one of emotion information, emphasis information, association information, prediction information, or task priority information [“Natural language component 405 may evaluate a mood of the user based on the content of a text message”; Jonsson; fig 4; para 0041 and 0063-0064].
Regarding claim 18, the combination of Jonsson-Jones further discloses the performing core semantic acquisition processing on the information source to obtain core semantic information comprises: inputting the information source into a sixth trained network model to obtain the core semantic information [ie. using machine learning (natural language component) to obtain contextual information (“core semantic information”); Jonsson; para 0041 and 0063-0066].
Regarding claims 19 and 20, the apparatus of claims 19 and 20 perform the similar steps as the apparatus of claims 10 and 11. The combination of Jonsson-Jones teaches the method of claims 10 and 11, as referenced above. The additional limitation of a broad “network device” is rejected with the citation of column 2, lines 45-55 and column 5, lines 12-34 of Jones. Therefore, claims 19 and 20 are rejected using the same art and rationale set forth above in the rejection of claims 10 and 11, by the teachings of combination of Jonsson-Jones.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Jonsson-Jones as applied to claim 16 above, and further in view of Van Dyke et al. (“Van Dyke”) [USPAT 11,170,154].
Regarding claim 17, the combination of Jonsson-Jones further discloses classifying each piece of information in the extended semantic information [Jonsson; para 0043, 0063, and 0068] but does not specifically disclose “using corresponding identifier information as a classification identifier” and “establishing a mapping relationship based on the classification identifier and a corresponding classification description”.
However, in the same field of endeavor, the Van Dyke reference discloses classifying semantic using corresponding identifier information as a classification identifier and establishing a mapping relationship based on the classification identifier and a corresponding classification description [Van Dyke; fig 5 and 6A; column 4, lines 31-63, col 23, lines 18-63, col 24, lines 25-50, and col 27, lines 53-67]. The Jonsson-Jones and Van Dyke references are analogous art, since they have similar problem solving area in being able to manage text message communications. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of classification identifier and mapping, taught by Van Dyke, into the system, taught by Jonsson-Jones. The motivation for doing so would have been to easily read the text message.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Nguyen et al. [USPAT 10,437,833] describes determining semantics in text messages.
Wang et al. [PGPUB 2023/0123271] describes decoding text message and determining meaning/emoticons of message.
Levy et al. [USPAT 10,013,654] describes a neural network with natural language processing.
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/JASON D CARDONE/Primary Examiner, Art Unit 2458
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