DETAILED ACTION
This Office action is responsive to the following communication: Application filed on 20 May 2025.
Claim(s) 1-12 is/are pending and present for examination. Claim(s) 1 is/are in independent form.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Drawings
The drawings were received on 20 May 2025. These drawings are accepted.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: various modules which are “configured to” in 1, 9, and 12.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The term “quickly” in claim 5 is a relative term which renders the claim indefinite. The term “quickly” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Appropriate clarification and/or correction is required.
Claim Rejections - 35 USC § 101
Claims 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-12 are directed to an intelligent communication secretary system for searching information and may be considered software per se as they fail to recite the use of any hardware components within the claim limitation. That is, the claims fail to recite the integration of the claimed features within a computer hardware system for execution. Therefore, since the claims simply recite but simply recite steps of implementation, said claims constitute non-statutory subject matter since they fail to fall within a statutory category.
Claim Rejections - 35 USC § 102
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 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)(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.
Claim(s) 1, 9, and 11 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Liu et al, USPGPUB No. 2021/0152506, filed on 20 November 2019, and published on 20 May 2021.
As per independent claim 1, Liu teaches:
An intelligent communication secretary system, applicable to being connected to a first communication system, the first communication system having a first interaction interface specific to a user comprising:
an intelligent interaction unit comprising an intelligent interaction module connected to the first interaction interface and an interaction outline generation module connected to the intelligent interaction module {See Liu, Figures 5A-5B};
a database unit comprising an account storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
a knowledge storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
a historical interaction storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B}, and
an outline data storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the account storage module being configured to store account data related to the first interaction interface in such a way that the intelligent interaction module is able to interact with the user by using the first interaction interface {See Liu, [0059], wherein this reads over “User profile module 420 may be configured to create and/or store user profiles. User profiles may include a configuration file for saving personal characteristics of users (e.g., such as a role as described herein) and/or user preferences. User profiles may also include information relating to user relationships, such as whether any users have or share job histories, education, social media connections, or the like.”},
the knowledge storage module being configured to store interaction knowledge of interaction with the user for the intelligent interaction module to interact with the user and generate a first interaction content {See Liu, [0063], wherein this reads over “Context monitor module 426 may be configured to monitor threads for new messages for analysis.”},
the historical interaction storage module being configured to store the first interaction content and make a same into a historical interaction content {See Liu, [0063], wherein this reads over “Log module 428 is configured to log all data for future reference, such that decisions of annotation manager module 408 (and/or of CHCML engine 400) may be later referenced as necessary”}, and
the interaction outline generation module analyzing the semantics of the historical interaction content and generating interaction outline data based on key semantic points, which is stored in the outline data storage module {See Liu, [0056], wherein this reads over “As described above, CHCML engine 400 may include criteria, rules, and/or factors for intelligently managing a chatting session from one or more chatting applications 112. CHCML engine 400 may be configured to define a data structure for monitoring, annotating, classifying, retrieving data for, filtering, grouping, and/or providing different layouts for multiple topics, conversation threads, and/or users. CHCML engine 400 is configured to identify user names and user roles, and to enable users to annotate new entries within an ongoing conversation thread, monitor this ongoing thread, view current users, topics, and chatting threads, detect a hierarchical relationship of corresponding conversation threads, and therein annotate any further messages that are not yet annotated. CHCML engine 400 can then classify chatting threads based on these annotated messages, retrieve messages or threads in response to prompts from users, display related messages adjacent each other (and therein filter out unrelated messages), or the like.”};
wherein the user inputs information into the intelligent interaction unit via the first interaction interface {See Liu, [0051], wherein this reads over “As depicted in FIG. 4, controller 110 may monitor text conversation 150 of users (300). There may be any number of users using any number of user devices 120 within text conversation 150. For example, as depicted in conversation 150 of FIG. 1B, controller 110 may monitor messages 152A-152K as sent by user devices 120 across network 140 via chatting application 112.”},
the intelligent interaction module interprets the information entered by the user, retrieves relevant data from the database unit based on the interpretation {See Liu, [0038], wherein this reads over “In some examples, controller 110 may be configured to identify that messages 152 are related even if these messages 152 occur across different communication methods. For example, as discussed above, controller 110 may monitor and analyze messages 152A-152K on one chatting application 112, for which controller 110 is a plugin or otherwise has access to analyze data. Controller 110 may further be configured to analyze communication across one or more other chatting applications 112, which may include email exchanges, text messages, or the like. As part of this, controller 110 may be configured to identify messages 152 from other chatting applications 112 as related to conversation 150.”}, and
the intelligent interaction module transmits the retrieval result back to the user through the first communication system {See Liu, [0038], wherein this reads over “In response to this, controller 110 may include this message 152L in chart 170 for this conversation 150. Further, in some examples controller 110 may be configured to include this message 152L in one or more relevant pop-up windows 164 or the like to display related messages 152 adjacent other messages 152.”}.
As per dependent claim 9, Liu teaches:
The intelligent communication secretary system according to claim 1,
wherein the intelligent interaction unit further comprises a knowledge augmentation module connected to the intelligent interaction module {See Liu, Figures 5A-5B}, and
the knowledge augmentation module is configured to augment the interaction knowledge in the knowledge augmentation module {See Liu, [0064], wherein this reads over “Classifier module 410 of CHCML engine 400 is configured to classify some or all threads based on the identified chatting relationship (e.g., identify a thread as a thread, and title it appropriately). Retriever module 412 is configured to retrieve messages that belong to a related thread based on a prompt of a user. For example, retriever module 412 may identify that a user requested to see all messages from a certain user for a certain topic on a certain thread, and may accordingly retrieve each of these threads for presentation.”}.
As per dependent claim 11, Liu teaches:
The intelligent communication secretary system according to claim 1,
wherein the intelligent interaction module is further connected to a data detection device outputting detection data {See Liu, Figures 5A-5B},
the intelligent interaction unit further comprises a detection analysis module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the detection analysis module stores detection judgment knowledge and analyzes and judges the detection data {See Liu, [0065], wherein this reads over “Unrelated entry filter module 414 may be configured to filter (e.g., remove from a display) some or all messages that are not related to one or more selected topics. Unrelated entry filter module 414 may filter away messages in response to a request from retriever module 412 to only display messages of a selected topic or the like”}, and
the intelligent interaction module interacts with the user in the first communication system based on a judgment result of the detection analysis module {See Liu, [0065], wherein this reads over “Unrelated entry filter module 414 may be configured to filter (e.g., remove from a display) some or all messages that are not related to one or more selected topics. Unrelated entry filter module 414 may filter away messages in response to a request from retriever module 412 to only display messages of a selected topic or the like”}.
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.
Claim(s) 2-6 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu, in view of Ben-Itzhak, USPGPUB No. 2017/0250930, filed on 11 January 2017, and published on 31 August 2017.
As per dependent claim 2, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 1,
wherein the intelligent communication secretary system is further connected to a second communication system {See Ben-Itzhak, [0030], wherein this reads over “For example, the user may be prompted to provide a voice sample via an interface of the interactive communication platform (e.g., “system A”). In an implementation, the voice sample may analyzed and converted into a dynamically generated, time-bound character string by system A (or the personalized content recommendation communication system) used to authenticate the user and gain access to the user's related user profile maintained by a related system (e.g., “system B”). The voice sample (e.g., one or more phrases or keywords) provided by the user is converted into a string and used by system A to query a user ID database of system B to identify one or more corresponding matches. Upon identifying one or more matches in system B, the corresponding user profile is provided by system B to system A for use in interacting with the user via system A, as described in detail below.”},
the intelligent interaction unit further comprises an account comparison module connected to the intelligent interaction module {See Ben-Itzhak, [0030], wherein this reads over “For example, the user may be prompted to provide a voice sample via an interface of the interactive communication platform (e.g., “system A”). In an implementation, the voice sample may analyzed and converted into a dynamically generated, time-bound character string by system A (or the personalized content recommendation communication system) used to authenticate the user and gain access to the user's related user profile maintained by a related system (e.g., “system B”). The voice sample (e.g., one or more phrases or keywords) provided by the user is converted into a string and used by system A to query a user ID database of system B to identify one or more corresponding matches. Upon identifying one or more matches in system B, the corresponding user profile is provided by system B to system A for use in interacting with the user via system A, as described in detail below.”},
the intelligent interaction module is connected to the second communication system, and the account comparison module obtains a comparison account from the second communication system and accesses to the account storage module for retrieval to confirm whether the first communication system has account data of a user of the second communication system {See Ben-Itzhak, [0030], wherein this reads over “For example, the user may be prompted to provide a voice sample via an interface of the interactive communication platform (e.g., “system A”). In an implementation, the voice sample may analyzed and converted into a dynamically generated, time-bound character string by system A (or the personalized content recommendation communication system) used to authenticate the user and gain access to the user's related user profile maintained by a related system (e.g., “system B”). The voice sample (e.g., one or more phrases or keywords) provided by the user is converted into a string and used by system A to query a user ID database of system B to identify one or more corresponding matches. Upon identifying one or more matches in system B, the corresponding user profile is provided by system B to system A for use in interacting with the user via system A, as described in detail below.”},
thereby enabling the intelligent interaction module to interact with the user via the second communication system {See Ben-Itzhak, [0030], wherein this reads over “For example, the user may be prompted to provide a voice sample via an interface of the interactive communication platform (e.g., “system A”). In an implementation, the voice sample may analyzed and converted into a dynamically generated, time-bound character string by system A (or the personalized content recommendation communication system) used to authenticate the user and gain access to the user's related user profile maintained by a related system (e.g., “system B”). The voice sample (e.g., one or more phrases or keywords) provided by the user is converted into a string and used by system A to query a user ID database of system B to identify one or more corresponding matches. Upon identifying one or more matches in system B, the corresponding user profile is provided by system B to system A for use in interacting with the user via system A, as described in detail below.”}.
Liu fails to expressly disclose the limitations of the instant claim. Ben-Itzhak is directed to the invention of an interactive content recommendation personalization assistant. Specifically, Ben-Itzhak discloses an environment comprising a plurality of systems (i.e., system A and system B). Furthermore, Ben-Itzhak provides that users are authenticated such that a user may gain access to the user’s related user profile maintained on a related system (i.e., obtains a comparison account from the second communication system and accesses to the account storage module for retrieval to confirm whether the first communication system has account data of a user of the second communication system). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the instant application to improve the prior art of Liu with that of Ben-Itzhak such that additional systems may be incorporated via connection such that user profiles may be retrieved as so disclosed by Ben-Itzhak. One of ordinary skill in the art would have been motivated to make the aforementioned combination such that users may easily communicate with a second system via their user profile.
As per dependent claim 3, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 2,
wherein the second communication system interacts with the user and generates a second interaction content {See Ben-Itzhak, [0032], wherein this reads over “In an implementation, information relating to a user may be collected and aggregated from multiple different user profiles (e.g., a user profile of the personalized content recommendation system and one or more related system) to form a primary user profile maintained by the personalized content recommendation communication system (herein the “primary user profile” or “Chatbot user profile”)”},
the historical interaction storage module stores the second interaction content and makes a same into a historical interaction content {See Ben-Itzhak, [0032], wherein this reads over “In an implementation, information relating to a user may be collected and aggregated from multiple different user profiles (e.g., a user profile of the personalized content recommendation system and one or more related system) to form a primary user profile maintained by the personalized content recommendation communication system (herein the “primary user profile” or “Chatbot user profile”)”}, and
the intelligent interaction module outputs the interaction outline data stored in the outline data storage module from the first interaction interface of the first communication system {See Liu, [0056], wherein this reads over “As described above, CHCML engine 400 may include criteria, rules, and/or factors for intelligently managing a chatting session from one or more chatting applications 112. CHCML engine 400 may be configured to define a data structure for monitoring, annotating, classifying, retrieving data for, filtering, grouping, and/or providing different layouts for multiple topics, conversation threads, and/or users. CHCML engine 400 is configured to identify user names and user roles, and to enable users to annotate new entries within an ongoing conversation thread, monitor this ongoing thread, view current users, topics, and chatting threads, detect a hierarchical relationship of corresponding conversation threads, and therein annotate any further messages that are not yet annotated. CHCML engine 400 can then classify chatting threads based on these annotated messages, retrieve messages or threads in response to prompts from users, display related messages adjacent each other (and therein filter out unrelated messages), or the like.”}.
As per dependent claim 4, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 2,
wherein the second communication system has a second interaction interface {See Ben-Itzhak, [0030], wherein this reads over “In this implementation, the user may be prompted to provide information or permission to allow the Chatbot system to access his or her related system ID and one or more user profiles maintained by another system, network, application, platform, or device (herein referred to as a “related profile”). In an embodiment, the user interacting with the interactive communication platform or the personalized content recommendation interactive communication platform is automatically prompted to provide information that may be used to identify the user and gain access to the one or more related user profiles maintained by one or more related systems.”},
the intelligent interaction module is connected to the second interaction interface {See Liu, Figures 5A-5B},
the intelligent interaction module uses the interaction knowledge stored in the knowledge storage module to interact with the user, the user inputs data through the second interaction interface, which transmits the data to the intelligent interaction module {See Ben-Itzhak, [0030], wherein this reads over “In this implementation, the user may be prompted to provide information or permission to allow the Chatbot system to access his or her related system ID and one or more user profiles maintained by another system, network, application, platform, or device (herein referred to as a “related profile”). In an embodiment, the user interacting with the interactive communication platform or the personalized content recommendation interactive communication platform is automatically prompted to provide information that may be used to identify the user and gain access to the one or more related user profiles maintained by one or more related systems.”},
the intelligent interaction module interprets the user's semantics and performs a retrieval from the database unit {See Ben-Itzhak, [0032], wherein this reads over “In an implementation, information relating to a user may be collected and aggregated from multiple different user profiles (e.g., a user profile of the personalized content recommendation system and one or more related system) to form a primary user profile maintained by the personalized content recommendation communication system (herein the “primary user profile” or “Chatbot user profile”)”}, and
the retrieval result is transmitted back to the user via the second interaction interface {See Ben-Itzhak, [0033], wherein this reads over “In an implementation, the personalized content recommendation system may further consider one or more content recommendation scopes in identifying or generating the one or more personalized content recommendations for a user.”}.
As per dependent claim 5, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 4,
wherein the intelligent interaction unit further comprises a knowledge retrieval module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the knowledge retrieval module stores at least one keyword, which is used to analyze the interaction knowledge stored in the knowledge storage module to obtain at least one knowledge fragment in the interaction knowledge and at least one fragment position for retrieving the knowledge fragment {See Liu, [0046], wherein this reads over “For example, in some embodiments, processor 220 may be configured to parse messages 152 from conversations 150 to determine semantic features (e.g., word meanings, repeated words, keywords, etc.) and/or syntactic features (e.g., word structure, location of semantic features in headings, title, etc.) of these messages 152. Ontological matching could be used to map semantic and/or syntactic features to a particular concept. The concept can then be used to determine the topic of each of messages 152. In this way, using NLP techniques 242, controller 110 may, e.g., identify a context of a given message 152 to therein match this message 152 to a given topic.”}, and
the fragment position is used for the intelligent interaction module to quickly obtain the knowledge fragment {See Liu, [0046], wherein this reads over “For example, in some embodiments, processor 220 may be configured to parse messages 152 from conversations 150 to determine semantic features (e.g., word meanings, repeated words, keywords, etc.) and/or syntactic features (e.g., word structure, location of semantic features in headings, title, etc.) of these messages 152. Ontological matching could be used to map semantic and/or syntactic features to a particular concept. The concept can then be used to determine the topic of each of messages 152. In this way, using NLP techniques 242, controller 110 may, e.g., identify a context of a given message 152 to therein match this message 152 to a given topic.”}.
As per dependent claim 6, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 5,
wherein the interaction knowledge stored in the knowledge storage module is selected from one or a combination of a text content, a picture content, a voice content and an audio and video content {See Liu, [0038], wherein this reads over “Controller 110 may further be configured to analyze communication across one or more other chatting applications 112, which may include email exchanges, text messages, or the like. As part of this, controller 110 may be configured to identify messages 152 from other chatting applications 112 as related to conversation 150. For example, controller 110 may identify an email message 152L from user A to user D with the content “Hey I can rake!” as related to the raking topic. In response to this, controller 110 may include this message 152L in chart 170 for this conversation 150. Further, in some examples controller 110 may be configured to include this message 152L in one or more relevant pop-up windows 164 or the like to display related messages 152 adjacent other messages 152.”}, and
the intelligent interaction module, based on the first interaction content of the first interaction interface, controls the knowledge retrieval module to access to the knowledge storage module or a network to retrieve the related text content, picture content, voice content and audio and video content and transmit a same to the second interaction interface {See Liu, [0038], wherein this reads over “Controller 110 may further be configured to analyze communication across one or more other chatting applications 112, which may include email exchanges, text messages, or the like. As part of this, controller 110 may be configured to identify messages 152 from other chatting applications 112 as related to conversation 150. For example, controller 110 may identify an email message 152L from user A to user D with the content “Hey I can rake!” as related to the raking topic. In response to this, controller 110 may include this message 152L in chart 170 for this conversation 150. Further, in some examples controller 110 may be configured to include this message 152L in one or more relevant pop-up windows 164 or the like to display related messages 152 adjacent other messages 152.”}.
As per dependent claim 12, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 1,
wherein the intelligent interaction module is further connected to a decision output device for outputting a decision instruction {See Liu, Figures 5A-5B},
the database unit further comprises a permission storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B}, and
the permission storage module is configured to store an execution permission related to the decision instruction and set the execution permission of the decision instruction as a priority in such a way that the intelligent interaction module prioritizes execution of the decision instruction {See Ben-Itzhak, [0070], wherein this reads over “In an implementation, if it is determined that the user session associated with the user includes a conversation history (i.e., a Chatbot user profile exists for the user), in block 307, the user session data including the conversation history is imported (e.g., by the user session manager 124 of FIG. 1) to a conversation engine (e.g., AI engine 122 or Rules-based engine 123 of FIG. 1). In block 309, the AI or rules-based engine generates one or more messages based on the user session data to provide to the user via the conversation agent. In an implementation, the AI or rules-based engine may analyze the user session data including messages received from the user during the active dialog with the conversation agent and the conversation history to generate the messages provided to the user.”}.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu, in view of Oldfield et al, USPGPUB No. 2022/0358462, filed on 10 May 2021, and published on 10 November 2022.
As per dependent claim 8, Liu, in combination with Ben-Itzhak, discloses:
The intelligent communication secretary system according to claim 1,
wherein the intelligent interaction unit further comprises a staff interaction module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the staff interaction module provides a professional staff to interact with the user and generates a professional interaction content {See Oldfield, [0027], wherein this reads over “In one implementation, the entity-level rules 118a comprise a plurality of parameters that define how the knowledge platform 104 should i) automatically perform context-based matching of the user and the current task to a set of experts selected from expert profiles stored in the contacts DB 120 to participate in the communication channel with the user, ii) determine how the dynamic communication channels 107 should be created, and iii) automatically perform context-based matching of the user and the current task to a set of knowledge articles 122c from the knowledge database 122 to recommend and return to the app 112”},
the intelligent interaction module stores the professional interaction content in the historical interaction storage module and makes a same into a historical interaction content {See Oldfield, [0078], wherein this reads over “For example, the Expert Assist chatbot may ask if the problem was resolved and if so how. Graham can then type in a solution, e.g., “I fixed the O-ring”, which is added to the knowledge database 122 to help other technicians in the future.”}, and
the intelligent interaction module learns and analyzes the historical interaction content and generates interaction knowledge stored in the knowledge storage module {See Oldfield, [0018], wherein this reads over “The knowledge repository 119 may further comprise an internal knowledge database 122A and a remote knowledge database 122B (collectively referred to as knowledge database 122) that store knowledge articles 122c. The knowledge articles 122c refer to collection of documentation that typically includes answers to frequently asked questions, how-to guides, and troubleshooting instructions. The purpose of the knowledge articles 122c is to make it easy for users to find solutions to their problems.”}.
Liu fails to expressly disclose the limitations of the instant claim. Oldfield is directed to a system for context and rule based dynamic communication channels for collaboration between users. Specifically, Oldfield discloses a system wherein users may be matched with experts (i.e., professional staff interacting with users to generate professional interaction content). See Oldfield, [0027]. Additionally, Oldfield discloses that additional data maybe added to the knowledge database at the conclusion of the interaction between a user and an expert (i.e., stores the professional interaction content). See Oldfield, [0078]. Lastly, Oldfield discloses that knowledge articles in the knowledge database may be further utilized in the future to address user inquiries (i.e., learn and analyze from the historical interaction content and generate interaction knowledge). One of ordinary skill in the art would have been motivated to make the aforementioned combination such that data verified by professionals may be generated and stored for future use, allowing for improved solutions.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu, in view of Le et al, USPGPUB No. 2024/0346251, filed on 13 April 2023, and published on 17 October 2024.
As per dependent claim 10, Liu, in combination with Le, discloses:
The intelligent communication secretary system according to claim 1,
wherein the intelligent interaction unit further comprises a calendar editing module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the database unit further comprises a calendar storage module connected to the intelligent interaction module {See Liu, Figures 5A-5B},
the calendar editing module analyzes data stored in the historical interaction storage module, extracts data related to a calendar and generates a calendar event {See Le, [0057], wherein this reads over “In one example, an add-on app be an application for automatically generating recommended calendar events and/or reminders, and so forth. Accordingly, the add-on app may subscribe to receive text-based messages that relate to a topic that is associated to scheduling, or messages having, as a message characteristic, text that expresses a date and/or time.”}, and
the intelligent interaction module edits a calendar content in the calendar storage module based on the calendar event {See Le, [0057], wherein this reads over “When the add-on app receives the messages, the add-on app may process the messages to generate recommended calendar events (e.g., meetings, appointments, reminders, tasks, etc.). The recommendations may be presented to a messaging participant in a user interface of the messaging application, with one or more buttons that enable the end-user to quickly accept the recommendation and add relevant event data to a calendar”}.
Liu fails to expressly disclose the limitations of the instant claim. Le is directed to a topic evaluation engine for a message service. Specifically, Le discloses that calendar events may be automatically generated based on related data (i.e., extract data related to a calendar and generate a calendar event). See Le, [0057]. Additionally, Le discloses that additional calendar events may be generated and presented to a user on a user interface (i.e., edit a calendar content). See Le, [0057]. It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the instant application to improve the prior art of Liu with that of Le such that user-related information and messages of Liu may be use to generate calendar events for the user according to the invention of Le. One of ordinary skill in the art would have been motivated to make the aforementioned combination such that calendar events may be easily gleaned and generated according to user data.
Allowable Subject Matter
Claim 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/Paul Kim/
Primary Examiner
Art Unit 2166
/PK/
Prosecution Insights