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 .
Response to Amendment
This is a Final Office Action in response to amendments received on 11/26/2025. Claims 1, 3, 6, 8-11, 13, 15, 17, and 19 have been amended. Claims 5, 7, 12, 14, 18, and 20 are cancelled. Claims 21-26 are new. Therefore, claims 1-4, 6, 8-11, 13, 15-17, 19 and 21-26 are pending and addressed below.
Claim Interpretation
Examiner notes that [0208]-[0217] provides definitions of various terms. Claims will be interpreted in view of these paragraphs.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 6, 8-11, 13, 15-17, 19 and 21-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Under step 1, claim 1 is directed to a method, claim 8 is directed to a system, and claim 15 is directed to a non-transitory machine-readable medium. Thus, claims 1, 8 and 15 are directed to statutory categories of patentable subject matter.
Step 2A, Prong One: Independent claim 1 recites, “detecting a commercial intent during a conversation between participants in a group chat and a chatbot of a chatbot system; and in response to detecting the commercial intent, performing operations comprising: extracting keyword candidates from the conversation based on at least one of a frequency of mention across a plurality of messages in the conversation, a context in which a keyword is mentioned, and relationships between the participants as determined from respective profiles of the participants; assigning a relevance score to each keyword candidate using a meaning of the conversation; assigning a commercial score to each keyword candidate using a machine learning model trained to detect commercially related keywords; selecting keywords using a combination of the relevance scores and commercial scores; detecting abusive language in the keywords; filtering the abusive language from the keywords before transmitting the keywords as filtered to one or more advertising content servers; receiving one or more advertisements from the one or more advertising content servers, the one or more advertisements selected by the one or more advertising content servers using the keywords as filtered; and providing, by the chatbot, the one or more advertisements to the participants of the group chat during the conversation.”
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity. The claimed invention detects a commercial intent, extract keyword candidates, assigns relevance scores, assigns commercial scores, select keywords, detect abusive language, filter the abusive language, transmits the selected keywords, receives one or more advertisements, and provides the advertisements which are advertising and marketing activities and behaviors since advertisements are provided based on the commercial intent detected in conversation.
The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Step 2A, Prong 2: This judicial exception is not integrated into a practical application. In particular, the independent claims recite the additional elements of “a chatbot system”, “a chatbot”, “a memory”, “a machine learning model”, “one or more advertising content servers”, “a non-transitory machine-readable medium”, and “one or more processors”, which are generic computing elements since they are recited at a high-level of generality (i.e., as a generic device performing a generic computer function) such that it amounts to no more than mere instructions to apply the exception using a computer. Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “a chatbot system”, “a chatbot”, “a memory”, “a machine learning model”, “one or more advertising content servers”, “a non-transitory machine-readable medium”, and “one or more processors” are generic computing elements and as such they are not significantly more than the abstract idea. Therefore, the claims are not patent eligible.
Dependent claims 2-4, 6, 9-11, 13, 16, 17, 19 and 21-26, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. §101 because the additional recited limitations fail to establish that the claims are not directed to the same abstract idea of Independent Claims 1, 8, and 15 without significantly more, as detailed above.
Claims 2, 9, and 16 recite, “further comprising: integrating the one or more advertisements into responses from the chatbot.” This limitation is part of the same abstract idea as the independent claims.
Claims 3, 10, and 17 recite, “wherein the advertisements are selected further using a predicted click-through rate for the user.” This is further limiting the advertisements of the independent claims and is part of the same abstract idea as the independent claims.
Claims 4 and 11 recite, “wherein the machine learning model is trained on data comprising translations of labeled examples from a first language into a second language.” Even though this is further limiting the machine learning model, the machine learning model is still generically recited and does not integrate the abstract idea into a practical application and is not significantly more than the abstract idea.
Claims 6, 13, and 19 recite, “further comprising: accessing, by the advertisement search component, user profile data to provide contextual information for assigning the commercial scores.” The accessing steps is also part of the same abstract idea as the independent claims. The advertisement search component is a generic computing element performing generic functions and does not integrate the abstract idea into a practical application and is not significantly more than the abstract idea for the same reasons as the independent claims.
Claims 21, 23, and 25 recite, “wherein determining the commercial intent comprises using binary classifier that determines whether a conversation expresses commercial intent.” This is further limiting the determining step of the independent claims and is part of the same abstract idea as the independent claims.
Claims 22, 24, and 26. “wherein extracting keyword candidates from the conversation further comprises: identifying phrases that appear frequently in the conversation; and favoring more frequently occurring phrases as keyword candidates.” This is further limiting the extracting step of the independent claims and is part of the same abstract idea as the independent claims.
As such, when claims 1-4, 6, 8-11, 13, 15-17, 19 and 21-26 are considered individually, as a whole, or in combinations, the claims are not patent eligible.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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 1-3, 6, 8-10, 13, 15-17, 19, 21, 23, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (U.S. Patent No. 11,158,311), in view of Price (WO2017209749), in further view of Kim (P. G. Pub. No. 2023/0216814).
Regarding claims 1, 8, and 15, Zhang teaches
1. (Currently Amended) A method comprising: (abstract)
8. (Currently Amended) A machine, comprising: one or more processors: and a memory storing instructions that, when executed by the one or more processors. cause the machine to perform operations comprising:
15. (Currently Amended) A non-transitory machine-readable medium storing instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising (Fig. 1 shows a Chatbot system, Column 3 lines 26-27 "The hardware device (110) comprises one or more processors."):
detecting a commercial intent during a conversation between participants in a group chat and a chatbot of a chatbot system; and in response to detecting the commercial intent, performing operations comprising (Column 8 lines 8-21 "In some embodiments, a machine as a computing device can have multiple current users. For example, two or more people can have a conversation or text chat or email with each other with the content of the conversation or chat being available to the machine [chatbot] as input. In such a case, the machine [intent determination component of the chatbot system] can listen or process the input in the background, and interject with appropriate response if certain intention [commercial intent] is detected from the conversation. For example, if one of the users [conversation between participants] says, "My cellphone is broken", and it is detected by the machine, then the machine can produce a response such as "Do you want me to recommend some cellphone deals for you?", or simply provide some information about cellphones without an initial suggestion."):
extracting keyword candidates from the conversation based on at least one of a frequency of mention across a plurality of messages in the conversation, a context in which a keyword is mentioned, and relationships between the participants as determined from respective profiles of the participants (Column 3 lines 31-36, "The input can be in voice or text format. Once the input is received, the input data is passed to a linguistic processing module (115), which analyzes the input expression by detecting terms [keyword] and their attributes, such as grammatical, semantic or contextual attributes [context in which a keyword is mentioned]." Column 8 lines 40-43 "A state with a source entity can be identified by analyzing terms [extract keyword candidates] in the input expression that represent a description or information about a physical or mental situation related to the source entity." See also Column 11 lines 15-31.);
assigning a relevance score to each keyword candidate using a meaning of the conversation (Fig. 2 "Importance Score" [relevance score] and "likelihood score" [commercial score] and Column 18 lines 25-32 "In FIG. 2, a use expression (205) is obtained, and is tokenized in to terms [candidate keywords] (210). Then, grammatical or semantic attributes associated with the terms are identified, and each term [each candidate keyword] can be assigned an importance score [relevance score] (215, 220) based on the grammatical or semantic attributes, such as whether the subject is a first person pronoun, or a third person pronoun, or whether the verb indicates an intention [meaning of the conversation] to purchase something, etc." Column 3 lines 31-40 explains that the linguistic analysis is done by the linguistic processing module [keyword extraction component of the chatbot system].);
assigning a commercial score to each keyword candidate using a machine learning model trained to detect commercially related keywords; selecting keywords using a combination of the relevance scores and commercial scores (Fig. 2 "Importance Score" [relevance score] and "likelihood score" [commercial score] and Column 18 lines 32-40 "Then, a likelihood score [commercial score] (225), (230) can be calculated for one or more terms [each keyword candidate] in the expression, or for the expression itself, which may contain one or more names of advertisable commodities. Then one or more terms [selecting keywords] can be selected (230) and output if the relevance score [combination of relevance score and commercial score] is above a threshold, and can be matched with an advertisement database. If one or more selected terms match an advertisement in the database, the advertisement can be displayed to the user." Column 8 lines 47-48 "using a pre-trained machine-learning model". See also Column 14 lines 34-55 and Column 19 lines 1-6.);
providing, by the chatbot, the one or more advertisements to the participants of the group chat during the conversation (Column 8 lines 8-21 "In some embodiments, a machine as a computing device can have multiple current users . For example, two or more people [participants of the group chat] can have a conversation or text chat or email with each other with the content of the conversation or chat [chatbot] being available to the machine as input. In such a case, the machine [intent determination component of the chatbot system] can listen or process the input in the background, and interject with appropriate response if certain intention [commercial intent] is detected from the conversation. For example, if one of the users [conversation between participants] says, "My cellphone is broken", and it is detected by the machine, then the machine can produce a response such as "Do you want me to recommend some cellphone deals for you?", or simply provide some information about cellphones [one or more advertisements] without an initial suggestion." Column 19 lines 31-37 "And if the word "computer" in sentence 310 matches a target keyword or the description of an advertisement associated with the commodity of computer, then such an advertisement can be displayed to the user either dynamically at the time the user makes an expression like sentence [during the conversation] 310." Column 3 lines 52-60 "If the likelihood value is above a threshold, then a response type can be selected from a data source according to the intention type (130). The response [advertisements] is output to the user interface (140) or other channels (105) [chatbot], and the response can be in either the voice, or text or video format, as part of the human-machine interaction [chatbot] (135), such that, the user can reply to the machine, or confirm a suggested action if the response contains a suggested action to be performed by the machine." See also Column 18 lines 1-18.).
Zhang transmit the keywords to the advertiser as explained above but not to one or more advertising content servers, and it is implicit that Zhang receives the advertisement that will be shown in the conversation. However, Zhang does not explicitly state that. Zhang does not expressly teach
detecting abusive language in the keywords;
filtering the abusive language from the keywords before transmitting the keywords as filtered to one or more advertising content servers;
receiving one or more advertisements from the one or more advertising content servers,
the one or more advertisements selected by the one or more advertising content servers using the keywords as filtered.
However, Price teaches
detecting ** language in the keywords; filtering the ** language from the keywords before transmitting the keywords as filtered to one or more advertising content servers (p. 4, 3rd par. "The parsing the message and identifying the one or more keywords can be performed by a first chat application [moderation component] of a first user." p. 5, 2nd par. "The chat application [advertisement search component] can filter the one or more identified keywords before sending the one or more identified keywords to the server. The chat application can filter the one or more keywords by cross-referencing a dictionary such that the one or more identified keywords sent to the server only include dictionary words of one or more desired types. The chat application can filter the one or more keywords by cross-referencing a blacklist such that the one or more identified keywords sent to the server [advertising content server] only include keywords not included in the blacklist." See also p. 9, 2nd par., p. 16, 2nd par. "negative keywords", and p. 19 last par.);
receiving one or more advertisements from the one or more advertising content servers, the one or more advertisements selected by the one or more advertising content servers using the keywords as filtered (p. 23, 3rd par. "The data processing system can include a link generation component 135 that provides the selected content item [advertisement] to the messaging application 155 to provide the selected content item along with the message. When the data processing system 120 (e.g., via the content selector component 130) selects a content item using one or more terms or keywords received from at least a portion of the message, the data processing system 120 (e.g., via link generation component 135) can provide the selected content item to the messaging application 155 for inclusion in the message.").
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the chat system of Zhang with the chat system of Price, by adding detecting ** language in the keywords; filtering the ** language from the keywords before transmitting the keywords as filtered to one or more advertising content servers; receiving one or more advertisements from the one or more advertising content servers, the one or more advertisements selected by the one or more advertising content servers using the keywords as filtered, as taught by Price, since Zhang and Price are analogous art, and in order to only include keywords of the desired types (p. 4, 3rd par.).
Zhang detects keywords and Price discusses filtering keywords that are on a blacklist in p. 5, 2nd par., filtering negative keywords in p. 16, 2nd par., and removing sensitive keywords in p. 19 last par. but not specifically that the keywords are “abusive language”. However, Kim teaches
abusive language in the keywords ([0008] "According to an aspect, there is provided a method of managing an abusing message, performed by an administrator terminal, the method including storing at least one of a rule set and a spam keyword for an abusing message, receiving a new message transmitted to an anonymous chatroom, determining the new message as the abusing message based on the at least one of the rule set and the spam keyword, and hiding the abusing message in a chat window. The administrator terminal may be configured to set activation of a function for hiding the abusing message through an interface distinguished from the chat window." See also [0053]-[0054].)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the chat systems of Zhang and Price with the chat system of Kim, by adding abusive language in the keywords, as taught by Kim, since Zhang, Price, and Kim are analogous art, in order to prepare countermeasures against various abusing messages ([0004).
Regarding claims 2, 9, and 16, Zhang teaches
further comprising: integrating the one or more advertisements into responses from the chatbot (Column 19 lines 31-37 "And if the word "computer" in sentence 310 matches a target keyword or the description of an advertisement associated with the commodity of computer, then such an advertisement can be displayed to the user either dynamically at the time the user makes an expression like sentence 310."Column 3 lines 52-60 "If the likelihood value is above a threshold, then a response type can be selected from a data source according to the intention type (130). The response [advertisements] is output to the user interface (140) or other channels (105), and the response can be in either the voice, or text or video format, as part of the human-machine interaction [chatbot] (135), such that, the user can reply to the machine, or confirm a suggested action if the response contains a suggested action to be performed by the machine." See also Column 18 lines 1-18.).
Regarding claims 3, 10, and 17, Zhang discusses displaying advertisements. Zhang discusses displaying highly relevant advertisements based on the price charged the advertiser in Column 26 lines 18-21.
Zhang does not explicitly teach
wherein the one or more advertisements are selected further using a predicted click-through rate.
However, Price teaches
wherein the one or more advertisements are selected further using a predicted click-through rate (p. 9, 3rd par. "The data processing system can take into account the content providers' per-click bid times to determine the predicted likelihood that the user will click on the content item. Thresholds may also be applied such that the data processing system can hyperlink only very high quality content. For example, the data processing system may only provide a hyperlink to content items having a predicted click-through rate above a certain threshold. The data processing system may only convert terms in a text message to a hyperlink if the hyperlinked content item has a click through rate above a threshold.").
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the chat system of Zhang with the chat system of Price by adding wherein the one or more advertisements are selected further using a predicted click-through rate, as taught by Price, since Zhang and Price are analogous art, and in order to hyperlink only very high quality content (Price, p. 9, 3rd par.)
Regarding claims 6, 13, and 19, Zhang teaches
further comprising: accessing user profile data to provide contextual information for assigning the commercial scores (Column 28 lines 10-16 "A dynamic user profile can be built up within a period of time when enough data is gathered, and the automatically detected topics of user interest can be added to the existing user profile to better serve the user or user community, such as making relevant recommendations or suggestion, as well as to better serve the commodity providers.").
Claims 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (U.S. Patent No. 11,158,311), ), in view of Price (WO2017209749), in view of Kim (P. G. Pub. No. 2023/0216814), in further view of Gao (P. G. Pub. No. 2013/0103493).
Regarding claims 4 and 11, Zhang discusses using a pre-trained machine learning model in Column 8 lines 47-48 and Price discusses using translation techniques on p. 27. Zhang, Price, and Kim do not specifically teach
wherein the machine learning model is trained on data comprising translations of labeled examples from a first language into a second language.
However, Gao teaches
wherein the machine learning model is trained on data comprising translations of labeled examples from a first language into a second language ([0019] "The training mechanism [machine learning model] 104 may utilize various data for the purpose of computing translation probabilities between a search query sub-language [first language] and a document/advertisement sub-language [second language], such as alignment templates 112 and/ or a word-aligned training corpus [labeled examples] 114. It is appreciated that while example embodiments of these translation probabilities involve a common language, such as English, each probability refers to a lexical gap between different words or phrases that often manifests within information retrieval systems. A search query term may map to different terms having identical or similar meanings and/or to multiple meanings being conveyed in various documents/advertisements.").
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the systems of Zhang, Price, and Kim with the system of Gao by adding wherein the machine learning model is trained on data comprising translations of labeled examples from a first language into a second language, as taught by Gao, since Zhang, Price, Kim and Gao are analogous art, in order to computer translation probabilities and to produce relevance scores (Gao, [0019] and abstract).
Claims 22, 24, and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (U.S. Patent No. 11,158,311), in view of Price (WO2017209749), in view of Kim (P. G. Pub. No. 2023/0216814), in further view of Xu (P. G. Pub. No. 2022/0171947).
Regarding claims 22, 24, and 26, Zhang, Price, and Kim do not specifically teach
wherein determining the commercial intent comprises using binary classifier that determines whether a conversation expresses commercial intent.
However, Xu teaches
wherein determining the commercial intent comprises using binary classifier that determines whether a conversation expresses commercial intent ([0058] "The intent classifier may use a binary cross-entropy loss function and a distance-based logit value as part of predicting the intent of the utterance. In this way, the distance refers to a distance calculated between the output vector of the intent classifier and a centroid for a particular intent. The logit values for the different intents thereafter serve as inputs to the loss functions included in the overall loss function of the model. For example, the overall loss function may include the binary cross-entropy loss term [binary classifier], a margin loss term, and a threshold loss term. In this way, the intent classifier may predict an intent when the most probable intent satisfies a minimum difference between the most probable and the second most probable intents, and when the most probable intent meets a minimum threshold confidence, related to a distance measurement from the centroids of the intents." See also [0047].).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the systems of Zhang, Price, and Kim with the system of Xu by adding wherein determining the commercial intent comprises using binary classifier that determines whether a conversation expresses commercial intent, as taught by Xu, since Zhang, Price, Kim, and Xu are analogous art, in order to improve the performance of the chatbot and the user experience with the chatbot (Xu, [0034]).
Response to Argument
All 112(a) rejections have been withdrawn because the claims are either amended or cancelled.
With regards to the 101, on p. 8, Applicant states, “In the Office Action, at Section 17, it is stated that the claims are "directed to 'mental processes' - concepts performed in the human mind (including an observation, evaluation, judgment, opinion). The steps of detecting commercial intent, extracting keyword candidates, assigning scores, selecting keywords, detecting abusive language, filtering, and receiving/providing advertisements can all be performed mentally or using pen and paper." Applicant respectfully disagrees that the claims are directed to mental processes that can all be performed in the human mind.” This argument is moot since Examiner did not say that the claims are directed to a mental process.
On p. 8-9, applicant restates the independent claims and states, “Applicant submits that a human mind cannot perform all of these operations during the time span of a conversation between participants in a group chat and a chatbot because of the complexity and interrelatedness of the operations. In addition, at least one of the operations includes communicating with content servers. Another of the operations includes assigning-a commercial score to each keyword candidate using a machine learning model. The operations are performed during the conversation in order to provide the one or more advertisements to the participants during the conversation. Accordingly, Applicant respectfully requests withdrawal of the rejection under 35 U.S.C. § 101.” Examiner respectfully disagrees. The claims do not require specific time span. The conversation could take place over several hours. As explained in the 101 rejection above, the content servers are an additional element that does not integrate the abstract idea into a practical application and is not significantly more because of the way they are generically recited. Therefore, Examiner is not persuaded.
On p. 10, Applicant points to Column 8 lines 8-21 of Zhang and states, “Applicant submits that Zhang does not describe or suggest at least the features of "extracting keyword candidates from the conversation based on at least one of a frequency of mention across all messages in the conversation, a context in which a keyword is mentioned, and relationships between the participants as determined from respective profiles of the participants," as recited in the amended claims.” Examiner respectfully disagrees. The claim recites “at least one of”, so only one of the limitations in the list are required. Zhang teaches “a context in which a keyword is mentioned”. See the updated 103 rejection above. Therefore, Examiner is not persuaded.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/MARIE P BRADY/Primary Examiner, Art Unit 3622