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 .
Notice for all Patent Application as subject to AIA
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
DETAILED ACTION
Claims 1-20 are presented for examination.
Claim Rejections - 35 USC § 102(a)(1)/102(a)(2)
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Ezrielev et al (U.S. Patent Application Publication No. 2024/0273800 A1).
Ezrielev’s patent application meets all the limitations for claims 1-20 recited in the claimed invention.
As to claim 1, Ezrielev et al teach a human-computer interaction method based on a historical conversation (figures 6-7, pars. 0075-0081, human-computer interaction based on session history data), comprising: acquiring current conversation information of a user and a historical conversation database; wherein the historical conversation database comprises a plurality of historical memory objects, the historical memory object represents historical conversation information of the user and an analysis result of the historical conversation information, the analysis result comprises a timestamp and semantic information of the historical conversation information (figure 4, pars. 0070-0071, figure 12, pars. 0131-0135, collecting current/historical session data, analyzing them and generating time information and recommending information); determining, from the historical conversation database, a historical memory object associated with the current conversation information as a target memory object; determining, according to the target memory object, response information of the current conversation information (figure 3, pars.0065-0069, figure 13, pars. 0137-0141, creating a target object and response).
As to claim 2, Ezrielev et al teach that determining an association value between each historical memory object and the current conversation information in the historical conversation database; wherein the association value represents an association degree between the historical memory object and the current conversation information; determining, according to the association value corresponding to each historical memory object, the target memory object from the historical conversation database (figure 6, pars. 0075-0076).
As to claim 3, Ezrielev et al teach that determining, according to a timestamp of the historical memory object, a distance value between the historical memory object and the current conversation information; wherein the distance value represents a time distance between the historical memory object and the current conversation information; determining, according to semantic information of the historical memory object, a correlation value between the historical memory object and the current conversation information; wherein the correlation value represents a semantic correlation degree between the historical conversation information represented by the historical memory object and the current conversation information; determining, according to the distance value and the correlation value corresponding to the historical memory object, the association value between the historical memory object and the current conversation information (figure4, pars. 0070-0071, figures 10-11, pars. 0094-0130).
As to claim 4, Ezrielev et al teach that a sentiment tag, and the sentiment tag represents an emotion expressed by the historical conversation information represented by the historical memory object; and the determining, according to the semantic information of the historical memory object, the correlation value between the historical memory object and the current conversation information comprises: performing sentiment analysis on the current conversation information to obtain sentiment information of the current conversation information; determining a similarity between the sentiment information of the current conversation information and the sentiment tag of the historical memory object; determining, according to the similarity, the correlation value between the historical memory object and the current conversation information (figure 1, par. 0040, figure 4, par. 0070, figure 9, par. 0086).
As to claim 5, Ezrielev et al teach that determining a sentence structure of the historical conversation information represented by the historical memory object; wherein the sentence structure represents grammar and a word order of the historical conversation information; determining an importance value of the historical memory object according to the sentence structure; wherein the importance value represents a degree of grammatical fluency and a degree of contextual importance of the historical conversation information represented by the historical memory object; determining, according to the distance value, the correlation value, and the importance value corresponding to the historical memory object, the association value between the historical memory object and the current conversation information (figures 6-7, pars. 0075-0079, figure 10, pars. 0094-0095, figure 13, pars. 0138-0141).
As to claim 6, Ezrielev et al teach that determining a number of occurrences of the historical conversation information represented by the historical memory object in the historical conversation database, adjusting, according to the number of occurrences, the importance value of the historical memory object (figure 2, par. 0062, figure 8, 0084-0085).
As to claim 7, Ezrielev et al teach that performing a weighted processing on the distance value, the correlation value, and the importance value corresponding to the historical memory object and determining a weighted processing result as the association value between the historical memory object and the current conversation information (figure 11, par. 0127-0128).
As to claim 8, Ezrielev et al teach that determining a sending time of the current conversation information, and determining the sending time as a timestamp of the current conversation information; performing a semantic analysis processing on the current conversation information to obtain semantic information of the current conversation information; determining the timestamp of the current conversation information and the semantic information of the current conversation information as an analysis result of the current conversation information; determining the current conversation information and the analysis result of the current conversation information as a new historical memory object, and storing the new historical memory object in the historical conversation database (figure 4, pars. 0070-0071, figure 12, pars. 0131-0135, collecting current/historical session data, analyzing them (session data) and generating time information and recommending information, and storing them (time/recommending information)).
As to claim 9, Ezrielev et al teach that determining, in the historical conversation database, a previous piece of conversation information of the current conversation information; marking a preset logical identifier in the current conversation information and the previous piece of conversation information of the current conversation information; wherein the preset logical identifier represents that there is a logical structure and a time sequence between two pieces of conversation information (pars. 0127-0130, figure 14, pars. 0145-0149).
As to claim 10, Ezrielev et al teach that by inputting the target memory object and the current conversation information into a preset large language model to obtain the response information of the current conversation information; wherein the preset large language model is a neural network model, used to converse with the user during human-computer interaction (figures 7-8, pars. 0079-0085).
As to claim 11, Ezrielev et al teach that acquiring, according to a preset information updating period, the timestamp of the historical memory object in the historical conversation database; if it is determined that a storage duration of the historical memory object in the historical conversation database exceeds a preset duration threshold according to the timestamp of the historical memory object, deleting the historical memory object from the historical conversation database (figure 4, pars. 0070-0071, figure 12, pars. 0131-0135, figure 15, par. 0150).
As to claims 12-19, they are also rejected for the same reasons set forth to rejecting claims 1-8 above, since claims 12-19 are merely an apparatus for the method of operations defined in the claims 1-8, and claims 12-19 do not teach or define any new limitations than rejected claims 1-8.
As to claim 20, it is also rejected for the same reasons set forth to rejecting claim 1 above, since claim 20 is merely a program product for the method of operations defined in claim 1, and claim 20 does not teach or define any new limitations than rejected claim 1.
Additional References
The examiner as of general interest cites the following references.
a. Southgate et al, U.S. Patent Application Publication No. 2025/0039234 A1.
b. El Hattami et al, U.S. Patent Application Publication No. 2024/0378393 A1.
c. Davis Jones et al, U.S. Patent No. 9,697198 B2.
Content Information
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/BHARAT BAROT/Primary Examiner, Art Unit 2453September 23, 2026
