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 .
DETAILED ACTION
This action is responsive to the amendment as filed on 3/18/2026.
This action is made Final.
Claims 1 – 20 are pending in the case. Claims 1, 11, and 20 are independent claims. Claims 1, 11 and 20 have been amended.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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(s) 1, 3-5, 9 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Angelis (USPUB 20190182384) in view of Mestanogullari (USPUB 20160182414 A1) and further in view of Brunn (USPUB 20190121907 A1).
Claim 1:
De Angelis teaches A computer-implemented method for converting electronic messages into conversation data (Abstract), the method comprising: receiving, by one or more processors and via an Application Programming Interface (API), electronic message data from an externally shared communication channel in a group-based communication platform, wherein the electronic message data comprises: a plurality of electronic messages; a respective user associated with each electronic message of the plurality of electronic messages; a respective channel or group associated with each electronic message; and a respective time or date associated with each electronic message (0042-45: the local agent may save each record with following attributes: conversation_id, user_id, relative_timestamp, audio file, and the like. When it is determined that the user has finished that portion of audio, in 212, the local agent determines whether the user thereof has authorized/consented to sharing of the local audio, in 214. Depending on whether the local user consented to sharing the audio will determine what is transmitted from the local agent to the host server. For example, when the local agent has been authorized to share the local audio file of the teleconference, in 216 the local agent saves/uploads the audio segment to the host server... The local agent may loads the local object by sending the audio segment of the user from the teleconference to the host server with various information. Here, each audio segment may contain the audio recording. The actual data being uploaded may be conversation_id, user_id, relative_timestamp, audio file... The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content. In some embodiments, the application ay include an application programming interface to make it easier for other software applications to retrieve the teleconference conversation data saved into the database); generating, by the one or more processors, a database that represents the electronic message data in a message per row format (Fig 4, 0044 and 0049: The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... Once a conversation has been uploaded to the host server, the host server may perform a post-conversation audio processing on the audio from the teleconference and transcript the speech to text. The textual information may be added to the database in a related record such as shown in table 410. In this table 410, each audio segment includes a conversation ID, a user ID, a host server time 411, and a device time 412, as well as other data such as file types for audio and text data); generating conversation data by grouping, by the one or more processors, the electronic messages in the database into one or more conversations based on the electronic message data (0049: The textual information may be added to the database in a related record such as shown in table 410. In this table 410, each audio segment includes a conversation ID); and outputting, by the one or more processors, the generated conversation data in a form of one or more of: a conversational HTML file; a text file; a CSV file containing each electronic message and respective metadata associated with each electronic message; a CSV file associated with each user associated with each electronic message; or a CSV file associated with each channel or group associated with each electronic message (0039, 0045, 0056: the local agent can optionally request text files (speech-to-text) from the host server 120 to elaborate on the details of the conversation... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content... In some embodiments, the method may further include converting speech from the plurality of local audio files to text, merging the converted text into chronological order to generate a single combined text file, and outputting the single combined text file along with the combined audio playback information. The text file can be helpful to a user listing to the combined audio because it can provide additional clarity. In some embodiments, the method may further include performing post-conversation processing on the converted text to remove words that are not of interest when generating the single combined text file to make the text easier and more compact to read).
De Angelis, by itself, does not seem to completely teach determining, by the one or more processors, whether a first subset of the electronic messages in the database fall into a same conversation as a second subset of the electronic messages in the database based on one or more conversation criteria; generating conversation data by grouping, by the one or more processors, the electronic messages in the database into the one or more conversations based on the electronic message data and the one or more conversation criteria, and wherein the one or more conversation criteria include (i) a time frame criteria based on an amount of time that has lapsed between electronic messages in the first subset and electronic messages in the second subset, and (ii) subject matter similarity between electronic messages in the first subset and electronic messages in the second subset determined via natural language processing; generating conversation data by grouping, by the one or more processors, the electronic messages in the database into the one or more conversations based on the electronic message data and the one or more conversation criteria, each of the one or more conversations comprising the one or more messages associated with the at least first respective user and the at least second respective user.
The Examiner maintains that these features were previously well-known as taught by Brunn.
Brunn teaches determining, by the one or more processors, whether a first subset of the electronic messages in the database fall into a same conversation as a second subset of the electronic messages in the database based on one or more conversation criteria; generating conversation data by grouping, by the one or more processors, the electronic messages in the database into the one or more conversations based on the electronic message data and the one or more conversation criteria, and wherein the one or more conversation criteria include (i) a time frame criteria based on an amount of time that has lapsed between electronic messages in the first subset and electronic messages in the second subset, and (ii) subject matter similarity between electronic messages in the first subset and electronic messages in the second subset determined via natural language processing; generating conversation data by grouping, by the one or more processors, the electronic messages in the database into the one or more conversations based on the electronic message data and the one or more conversation criteria, each of the one or more conversations comprising the one or more messages associated with the at least first respective user and the at least second respective user (0021, 0031-33 and 0035: within an organization, a development team may be working to develop a new product. The development team may use the group messaging system to exchange ideas, make decisions regarding product design, supply-chain, and release dates for the product, and perform any type of collaborative work related to the product or other facets of their team. This information can then be relied on at a later point in time to review decisions that have been made, or simply to explore previous discussions about a particular topic. Users of such group messaging systems may belong to a number of different teams that use the group messaging system to discuss and correspond in regards to different topics... multiple messages of a corpus are grouped (block 101) into a number of message bursts. During a correspondence within a group messaging system, different users may input messages via text, audio, or video to be shared with other users of the system. Additional content such as documents, audio files, image files, video files, etc. may also be shared between users in these group messaging systems. The messages within a particular working group of the group messaging system may be sent over hours, days, or even weeks. Groups of these messages can be grouped (block 101) into message bursts based on at least a temporal relationship. Accordingly, each message burst includes a number of messages that have at least a temporal relationship. In grouping (block 101) messages into message bursts, an interaction on a particular topic at a particular time is captured... The messages in the corpus that are to be grouped into message bursts will be the same for all users within a particular conversation. Accordingly, in some examples, grouping (block 101) of the messages to message bursts may occur as messages arrive. In another example, the grouping (block 101) occurs periodically, for example after a predetermined period of time... Such grouping (block 101) may be based on any number of factors. For example, the messages may be grouped (block 101) based on an inter-message interval time. That is, messages that have shorter inter-message intervals are more likely to relate to the same topic. Accordingly, a threshold inter-message interval time may be selected and adjacent messages that have an inter-message interval that is less than the threshold may be grouped into a message burst. If adjacent messages have an inter-message interval that is greater than the threshold value, the former message may be placed in a first message burst and the latter message may be grouped in a second message burst. The inter-message interval threshold may depend on the activity within the conversation... a textual analysis may be carried out on the messages as they arrive and adjacent messages that are determined to have the same topic may be joined to the same message burst. For example, Latent Dirichlet Allocation (LDA) could be used to discover topics from messages. Such a system may analyze multiple messages to determine whether those messages relate to the same topic or not. In one example, topics are calculated for individual messages, and/or for some number of trailing messages which are candidates for inclusion in a particular burst).
De Angelis and Brunn are analogous art because they are from the same problem-solving area, managing messages in a user messaging system.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Brunn before him or her, to combine the teachings of De Angelis and Brunn. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Brunn to obtain the invention as specified in the instant claim(s).
De Angelis and Brunn do not seem to completely teach wherein the first subset of the electronic messages includes one or more electronic messages associated with at least a first respective user, and the second subset of the electronic messages includes one or more electronic messages associated with at least a second respective user different from the first respective user.
The Examiner maintains that these features were previously well-known as taught by Mestanogullari.
Mestanogullari teaches wherein the first subset of the electronic messages includes one or more electronic messages associated with at least a first respective user, and the second subset of the electronic messages includes one or more electronic messages associated with at least a second respective user different from the first respective user (0050-52: a messaging client may organize groups of messages in conversation threads. A messaging client may also organize groups of messages by category, topic, and/or other distinguishing characteristic of a group of messages... the method may involve receiving additional messages from other users of the first communication system. In an embodiment, a second message sent by a second external messaging service user may be received... When it is determined that the second conversation thread does not exist the messaging client may trigger, based on the receipt of the broadcast second message, a generation of the conversation thread associated with the second user... The first conversation thread grouping messages associated with the first user, and the second conversation thread grouping messages associated with the second user).
De Angelis and Mestanogullari are analogous art because they are from the same problem-solving area, managing messages in a user messaging system.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Mestanogullari before him or her, to combine the teachings of De Angelis and Mestanogullari. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Mestanogullari to obtain the invention as specified in the instant claim(s).
Claim 3:
De Angelis discloses the grouping of the electronic messages includes: representing each of the plurality of electronic messages as one or more features, the one or more features at least including a time frame associated with each message; performing a clustering operation on the plurality of electronic messages based on the one or more features to identify one or more clusters of messages corresponding to one or more conversations; and wherein the conversation data for each conversation includes the electronic messages from one of the one or more clusters of messages corresponding to each conversation (0042-45: the local agent may save each record with following attributes: conversation_id, user_id, relative_timestamp, audio file, and the like. When it is determined that the user has finished that portion of audio, in 212, the local agent determines whether the user thereof has authorized/consented to sharing of the local audio, in 214. Depending on whether the local user consented to sharing the audio will determine what is transmitted from the local agent to the host server. For example, when the local agent has been authorized to share the local audio file of the teleconference, in 216 the local agent saves/uploads the audio segment to the host server... The local agent may loads the local object by sending the audio segment of the user from the teleconference to the host server with various information. Here, each audio segment may contain the audio recording. The actual data being uploaded may be conversation_id, user_id, relative_timestamp, audio file... The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content. In some embodiments, the application ay include an application programming interface to make it easier for other software applications to retrieve the teleconference conversation data saved into the database).
Claim 4:
De Angelis discloses the grouping of the electronic messages into one or more conversations is further based on a time frame criteria (0036, 0044: The host server 120 receives local audio files from all local agents/users who have authorized participation. The host server 120 may construct a single audio playback order for segments of audio within each local audio file by synchronizing the audio segments from the local audio files in chronological order. The host server 120 may perform audio processing to create a single audio playback order/queue (i.e., combined speech from all received local audio files) based on timestamp data in the plurality of local audio files...Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like).
Claim 5:
De Angelis discloses the time frame criteria is based on inactivity time or an amount of time that has lapsed between electronic messages (0036-37: The host server 120 receives local audio files from all local agents/users who have authorized participation. The host server 120 may construct a single audio playback order for segments of audio within each local audio file by synchronizing the audio segments from the local audio files in chronological order. The host server 120 may perform audio processing to create a single audio playback order/queue (i.e., combined speech from all received local audio files) based on timestamp data in the plurality of local audio files...Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... even if there is some overlap between two audio segments of two different users during the live teleconference, the host server 120 can see to it that there is no overlap when it generates the queue for playing back the audio. To do so, the host server 120 may modify an actual timing of an audio segment such that it does not overlap with an actual timing of a previous audio segment).
Claim 9:
De Angelis discloses wherein the one or more of the conversational HTML file, the conversational text file, the CSV file associated with each user, the CSV file containing each electronic message and respective metadata associated with each electronic message, or the CSV file associated with each channel or group, are viewable and editable using standard word processing software (0056: The text file can be helpful to a user listing to the combined audio because it can provide additional clarity. In some embodiments, the method may further include performing post-conversation processing on the converted text to remove words that are not of interest when generating the single combined text file to make the text easier and more compact to read).
Claim 20:
Claim 20 essentially recites a system for completing the steps of claim 1. As De Angelis discusses a system as claimed (Fig 1), claim 20 is rejected over De Angelis in view of Brunn and Mestanogullari and using the same rationale used above in the rejection of claim 1.
Claim(s) 2 and 6-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Angelis, Brunn and Mestanogullari, in view of “How to collect from Slack Enterprise – Learn how to connect and collect from Slack’s Discovery API using Onna”, William Sears, Onna Help Center, Updated 2022 from IDS filed 6/16/2022 hereinafter Sears).
Claim 2:
De Angelis in view of Brunn and Mestanogullari teaches every feature of claim 1.
De Angelis, by itself, does not seem to completely teach receiving, by one or more processors, electronic text message data from an instant electronic text messaging application separate from the externally shared communication channel in the group-based communication platform, wherein the electronic text message data comprises: a plurality of electronic text messages; a respective user associated with each electronic text message of the plurality of electronic text messages; one or more respective recipients associated with each electronic text message; and a respective time or date associated with each electronic text message; generating, by the one or more processors, a second database that represents the electronic text message data in a message per row format, wherein generating the conversation data by grouping the electronic messages into one or more conversations further comprises grouping, by the one or more processors, the electronic messages in the database and the plurality of electronic text messages in the second database together into one or more conversations.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches receiving, by one or more processors, electronic text message data from an instant electronic text messaging application separate from the externally shared communication channel in the group-based communication platform, wherein the electronic text message data comprises: a plurality of electronic text messages; a respective user associated with each electronic text message of the plurality of electronic text messages; one or more respective recipients associated with each electronic text message; and a respective time or date associated with each electronic text message; generating, by the one or more processors, a second database that represents the electronic text message data in a message per row format, wherein generating the conversation data by grouping the electronic messages into one or more conversations further comprises grouping, by the one or more processors, the electronic messages in the database and the plurality of electronic text messages in the second database together into one or more conversations (pages 12-13 and 16-22: there is discussion of being able to configure message retrieval and synchronization across various channels and direct or multiparty messages, with the messages being added to an Onna database. The Onna database can then be browsed via a user interface, with conversations being saved as HTML files, the naming convention being type of chat, name of channel or person, the participants and date).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 6:
De Angelis, by itself, does not seem to completely teach generating, by the one or more processors, a unique sequence value for each electronic message stored on the database based on the respective metadata associated with each electronic message.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches generating, by the one or more processors, a unique sequence value for each electronic message stored on the database based on the respective metadata associated with each electronic message (page 16: “the standard title for chat files will be: type of chat...name of the channel or person...the participants...and date”).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have a unique file name for each generated file.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 7:
De Angelis, by itself, does not seem to completely teach determining, by the one or more processors, whether an electronic message stored on the database is a duplicate message based on the unique sequence value; and upon determining that an electronic message is a duplicate message, removing the duplicate message from the database.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches determining, by the one or more processors, whether an electronic message stored on the database is a duplicate message based on the unique sequence value; and upon determining that an electronic message is a duplicate message, removing the duplicate message from the database (page 2: “auto-sync & archive means that Onna will perform a full sync first and will continuously add any new files generated at the data source”; the process of synchronization includes continuously adding new files after doing a full synch, which would inherently involved removal of any duplicate messages added during the full synchronization of all messages to ensure only new files are added).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have a unique file name for each generated file.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 8:
De Angelis, by itself, does not seem to completely teach the electronic message data comprises edit history information associated with each electronic message.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches the electronic message data comprises edit history information associated with each electronic message (pages 17-18: “if you have keep everything as a setting across public channels, and direct messages in your workspace...you will be able to see edited and deleted messages in Onna...Onna also started adding “has deletions” or “has edits” on conversations that have had deletes or edits. You can easily search for conversations that have been modified by searching “has edits” or “has:deletions”).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have an accurate representation of all messages present in the database.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Angelis, Yang, Mestanogullari in view of Coppersmith (USPAT 11468242).
Claim 10:
De Angelis in view of Yang and Mestanogullari teaches every feature of claim 1.
De Angelis, by itself, does not seem to completely teach grouping the electronic messages into one or more conversations further includes using a trained machine learning model, wherein the trained machine learning model has been trained based on (i) training electronic message data that includes information regarding one or more electronic messages associated with the training electronic message data and (ii) training conversation data that includes a prior category for each of the one or more electronic messages, to learn relationships between the training electronic message data and the training conversation data, such that the trained machine learning model is configured to use the learned relationships to determine a respective conversation for each electronic message in response to input of the plurality of electronic messages and data related to the plurality of electronic messages.
The Examiner maintains that these features were previously well-known as taught by Coppersmith.
Coppersmith teaches grouping the electronic messages into one or more conversations further includes using a trained machine learning model, wherein the trained machine learning model has been trained based on (i) training electronic message data that includes information regarding one or more electronic messages associated with the training electronic message data and (ii) training conversation data that includes a prior category for each of the one or more electronic messages, to learn relationships between the training electronic message data and the training conversation data, such that the trained machine learning model is configured to use the learned relationships to determine a respective conversation for each electronic message in response to input of the plurality of electronic messages and data related to the plurality of electronic messages (Col 8 ln 66-Col 9 ln 4: The software may use machine-learning techniques. It may be trained on a large corpus of messages. As the software monitors each team, its analyses may be used as outcomes for training and evaluating a model of emotional load or CAL for teams, and validating, adapting, and improving the machine learning algorithms; Claim 1: evaluating free-form text messages among team members of a team, using natural language processing techniques to process the text messages and to assess psychological state of the team members as reflected in the text messages; by the computer, assembling the psychological state of the team members as reflected in the text messages to evaluate team collective psychological state; in a memory of the computer, grouping the text messages into predetermined psychological state categories by determined emotion and/or sentiment of each of the text messages, the predetermined psychological state categories comprise more than one category of emotion and more than one category of sentiment).
De Angelis and Coppersmith are analogous art because they are from the same problem-solving area, storing messages sent between users and grouping them.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Coppersmith before him or her, to combine the teachings of De Angelis and Coppersmith. The rationale for doing so would have been to enhance the message grouping process to make it more accurate and efficient.
Therefore, it would have been obvious to combine De Angelis and Coppersmith to obtain the invention as specified in the instant claim(s).
Claim(s) 11-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Angelis in view of Sears and Brunn, and further in view of Coppersmith (USPAT 11468242) and Mestanogullari.
Claim 11:
De Angelis teaches A computer-implemented method for converting electronic messages into conversation data (Abstract), the method comprising: receiving, by one or more processors and via an Application Programming Interface (API), electronic message data from an externally shared communication channel in a group-based communication platform, wherein the electronic message data comprises: a plurality of electronic messages; a respective user associated with each electronic message of the plurality of electronic messages; a respective channel or group associated with each electronic message; and a respective time or date associated with each electronic message (0042-45: the local agent may save each record with following attributes: conversation_id, user_id, relative_timestamp, audio file, and the like. When it is determined that the user has finished that portion of audio, in 212, the local agent determines whether the user thereof has authorized/consented to sharing of the local audio, in 214. Depending on whether the local user consented to sharing the audio will determine what is transmitted from the local agent to the host server. For example, when the local agent has been authorized to share the local audio file of the teleconference, in 216 the local agent saves/uploads the audio segment to the host server... The local agent may loads the local object by sending the audio segment of the user from the teleconference to the host server with various information. Here, each audio segment may contain the audio recording. The actual data being uploaded may be conversation_id, user_id, relative_timestamp, audio file... The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content. In some embodiments, the application ay include an application programming interface to make it easier for other software applications to retrieve the teleconference conversation data saved into the database); generating, by the one or more processors, a database that represents the electronic message data in a message per row format (Fig 4, 0044 and 0049: The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... Once a conversation has been uploaded to the host server, the host server may perform a post-conversation audio processing on the audio from the teleconference and transcript the speech to text. The textual information may be added to the database in a related record such as shown in table 410. In this table 410, each audio segment includes a conversation ID, a user ID, a host server time 411, and a device time 412, as well as other data such as file types for audio and text data); generating conversation data by grouping, by the one or more processors, the electronic messages in the database into one or more conversations based on the electronic message data (0049: The textual information may be added to the database in a related record such as shown in table 410. In this table 410, each audio segment includes a conversation ID); and outputting, by the one or more processors, the generated conversation data in a form of one or more of: a conversational HTML file; a text file; a CSV file containing each electronic message and respective metadata associated with each electronic message; a CSV file associated with each user associated with each electronic message; or a CSV file associated with each channel or group associated with each electronic message (0039, 0045, 0056: the local agent can optionally request text files (speech-to-text) from the host server 120 to elaborate on the details of the conversation... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content... In some embodiments, the method may further include converting speech from the plurality of local audio files to text, merging the converted text into chronological order to generate a single combined text file, and outputting the single combined text file along with the combined audio playback information. The text file can be helpful to a user listing to the combined audio because it can provide additional clarity. In some embodiments, the method may further include performing post-conversation processing on the converted text to remove words that are not of interest when generating the single combined text file to make the text easier and more compact to read).
De Angelis, by itself, does not seem to completely teach receiving, by one or more processors, electronic text message data from an instant electronic text messaging application separate from the externally shared communication channel in the group-based communication platform; generating conversation data by grouping, by the one or more processors, using a trained machine learning model, the electronic messages and electronic text messages in the database together into one or more conversations based on the electronic message data and electronic text message data, the grouping including performing a clustering operation on the plurality of electronic messages based on the one or more features to identify one or more clusters of messages corresponding to one or more conversations by identifying subject matter similarity between electronic messages via natural language processing.
The Examiner maintains that these features were previously well-known as taught by Sears, Coppersmith, Brunn and Mestanogullari.
Sears teaches receiving, by one or more processors, electronic text message data from an instant electronic text messaging application separate from the externally shared communication channel in the group-based communication platform; generating conversation data by grouping, by the one or more processors, the electronic messages and electronic text messages in the database together into one or more conversations based on the electronic message data and electronic text message data (pages 12-13 and 16-22: there is discussion of being able to configure message retrieval and synchronization across various channels and direct or multiparty messages, with the messages being added to an Onna database. The Onna database can then be browsed via a user interface, with conversations being saved as HTML files, the naming convention being type of chat, name of channel or person, the participants and date).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
De Angelis and Sears do not seem to completely teach generating conversation data by grouping, by the one or more processors, using a trained machine learning model, the electronic messages and electronic text messages in the database together into one or more conversations based on the electronic message data and electronic text message data, the grouping including performing a clustering operation on the plurality of electronic messages based on the one or more features to identify one or more clusters of messages corresponding to one or more conversations.
The Examiner maintains that these features were previously well-known as taught by Coppersmith and Brunn.
Coppersmith teaches generating conversation data by grouping, by the one or more processors, using a trained machine learning model, the electronic messages and electronic text messages in the database together into one or more conversations based on the electronic message data and electronic text message data (Col 8 ln 66-Col 9 ln 4: The software may use machine-learning techniques. It may be trained on a large corpus of messages. As the software monitors each team, its analyses may be used as outcomes for training and evaluating a model of emotional load or CAL for teams, and validating, adapting, and improving the machine learning algorithms; Claim 1: evaluating free-form text messages among team members of a team, using natural language processing techniques to process the text messages and to assess psychological state of the team members as reflected in the text messages; by the computer, assembling the psychological state of the team members as reflected in the text messages to evaluate team collective psychological state; in a memory of the computer, grouping the text messages into predetermined psychological state categories by determined emotion and/or sentiment of each of the text messages, the predetermined psychological state categories comprise more than one category of emotion and more than one category of sentiment).
De Angelis and Coppersmith are analogous art because they are from the same problem-solving area, storing messages sent between users and grouping them.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Coppersmith before him or her, to combine the teachings of De Angelis and Coppersmith. The rationale for doing so would have been to enhance the message grouping process to make it more accurate and efficient.
Therefore, it would have been obvious to combine De Angelis and Coppersmith to obtain the invention as specified in the instant claim(s).
De Angelis in view of Sears and Coppersmith does not seem to completely teach the grouping including performing a clustering operation on the plurality of electronic messages based on the one or more features to identify one or more clusters of messages corresponding to one or more conversations by identifying subject matter similarity between electronic messages via natural language processing.
The Examiner maintains that these features were previously well-known as taught by Brunn.
Brunn teaches the grouping including performing a clustering operation on the plurality of electronic messages based on the one or more features to identify one or more clusters of messages corresponding to one or more conversations by identifying subject matter similarity between electronic messages via natural language processing (0021, 0031-33 and 0035: within an organization, a development team may be working to develop a new product. The development team may use the group messaging system to exchange ideas, make decisions regarding product design, supply-chain, and release dates for the product, and perform any type of collaborative work related to the product or other facets of their team. This information can then be relied on at a later point in time to review decisions that have been made, or simply to explore previous discussions about a particular topic. Users of such group messaging systems may belong to a number of different teams that use the group messaging system to discuss and correspond in regards to different topics... multiple messages of a corpus are grouped (block 101) into a number of message bursts. During a correspondence within a group messaging system, different users may input messages via text, audio, or video to be shared with other users of the system. Additional content such as documents, audio files, image files, video files, etc. may also be shared between users in these group messaging systems. The messages within a particular working group of the group messaging system may be sent over hours, days, or even weeks. Groups of these messages can be grouped (block 101) into message bursts based on at least a temporal relationship. Accordingly, each message burst includes a number of messages that have at least a temporal relationship. In grouping (block 101) messages into message bursts, an interaction on a particular topic at a particular time is captured... The messages in the corpus that are to be grouped into message bursts will be the same for all users within a particular conversation. Accordingly, in some examples, grouping (block 101) of the messages to message bursts may occur as messages arrive. In another example, the grouping (block 101) occurs periodically, for example after a predetermined period of time... Such grouping (block 101) may be based on any number of factors. For example, the messages may be grouped (block 101) based on an inter-message interval time. That is, messages that have shorter inter-message intervals are more likely to relate to the same topic. Accordingly, a threshold inter-message interval time may be selected and adjacent messages that have an inter-message interval that is less than the threshold may be grouped into a message burst. If adjacent messages have an inter-message interval that is greater than the threshold value, the former message may be placed in a first message burst and the latter message may be grouped in a second message burst. The inter-message interval threshold may depend on the activity within the conversation... a textual analysis may be carried out on the messages as they arrive and adjacent messages that are determined to have the same topic may be joined to the same message burst. For example, Latent Dirichlet Allocation (LDA) could be used to discover topics from messages. Such a system may analyze multiple messages to determine whether those messages relate to the same topic or not. In one example, topics are calculated for individual messages, and/or for some number of trailing messages which are candidates for inclusion in a particular burst).
De Angelis and Brunn are analogous art because they are from the same problem-solving area, managing messages in a user messaging system.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Brunn before him or her, to combine the teachings of De Angelis and Brunn. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Brunn to obtain the invention as specified in the instant claim(s).
De Angelis and Brunn do not seem to completely teach wherein the electronic messages includes one or more electronic messages associated with at least a first respective user, and the electronic text messages includes one or more electronic text messages associated with at least a second respective user different from the first respective user.
The Examiner maintains that these features were previously well-known as taught by Mestanogullari.
Mestanogullari teaches wherein the electronic messages includes one or more electronic messages associated with at least a first respective user, and the electronic text messages includes one or more electronic text messages associated with at least a second respective user different from the first respective user (0050-52: a messaging client may organize groups of messages in conversation threads. A messaging client may also organize groups of messages by category, topic, and/or other distinguishing characteristic of a group of messages... the method may involve receiving additional messages from other users of the first communication system. In an embodiment, a second message sent by a second external messaging service user may be received... When it is determined that the second conversation thread does not exist the messaging client may trigger, based on the receipt of the broadcast second message, a generation of the conversation thread associated with the second user... The first conversation thread grouping messages associated with the first user, and the second conversation thread grouping messages associated with the second user).
De Angelis and Mestanogullari are analogous art because they are from the same problem-solving area, managing messages in a user messaging system.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Mestanogullari before him or her, to combine the teachings of De Angelis and Mestanogullari. The rationale for doing so would have been to allow for collecting and synchronizing messages across various channels and communication methods.
Therefore, it would have been obvious to combine De Angelis and Mestanogullari to obtain the invention as specified in the instant claim(s).
Claim 12:
De Angelis teaches wherein the electronic text message data comprises: a plurality of electronic text messages; a respective user associated with each electronic text message of the plurality of electronic text messages; one or more respective recipients associated with each electronic text message; and a respective time or date associated with each electronic text message (0042-45: the local agent may save each record with following attributes: conversation_id, user_id, relative_timestamp, audio file, and the like. When it is determined that the user has finished that portion of audio, in 212, the local agent determines whether the user thereof has authorized/consented to sharing of the local audio, in 214. Depending on whether the local user consented to sharing the audio will determine what is transmitted from the local agent to the host server. For example, when the local agent has been authorized to share the local audio file of the teleconference, in 216 the local agent saves/uploads the audio segment to the host server... The local agent may loads the local object by sending the audio segment of the user from the teleconference to the host server with various information. Here, each audio segment may contain the audio recording. The actual data being uploaded may be conversation_id, user_id, relative_timestamp, audio file... The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content. In some embodiments, the application ay include an application programming interface to make it easier for other software applications to retrieve the teleconference conversation data saved into the database).
Claim 13:
De Angelis teaches the grouping of the electronic messages includes: representing each of the plurality of electronic messages as one or more features, the one or more features at least including a time frame associated with each message; and wherein the conversation data for each conversation includes the electronic messages from the corresponding cluster (0042-45: the local agent may save each record with following attributes: conversation_id, user_id, relative_timestamp, audio file, and the like. When it is determined that the user has finished that portion of audio, in 212, the local agent determines whether the user thereof has authorized/consented to sharing of the local audio, in 214. Depending on whether the local user consented to sharing the audio will determine what is transmitted from the local agent to the host server. For example, when the local agent has been authorized to share the local audio file of the teleconference, in 216 the local agent saves/uploads the audio segment to the host server... The local agent may loads the local object by sending the audio segment of the user from the teleconference to the host server with various information. Here, each audio segment may contain the audio recording. The actual data being uploaded may be conversation_id, user_id, relative_timestamp, audio file... The host server may record the voice files (mpeg, way, etc.) into the database in the form of a blob, or the like, in 220. Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... The local agent can optionally request a speech-to-text file generated by the server (e.g., in 220) for textual elaboration of the teleconference conversation content. In some embodiments, the application ay include an application programming interface to make it easier for other software applications to retrieve the teleconference conversation data saved into the database).
Claim 14:
De Angelis discloses the grouping of the electronic messages and electronic text messages together into one or more conversations is further comprises grouping the electronic messages and electronic text messages into one or more conversations based on a time frame criteria (0036, 0044: The host server 120 receives local audio files from all local agents/users who have authorized participation. The host server 120 may construct a single audio playback order for segments of audio within each local audio file by synchronizing the audio segments from the local audio files in chronological order. The host server 120 may perform audio processing to create a single audio playback order/queue (i.e., combined speech from all received local audio files) based on timestamp data in the plurality of local audio files...Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like).
Claim 15:
De Angelis discloses the time frame criteria is based on inactivity time or an amount of time that has lapsed between electronic messages and/or electronic text messages (0036-37: The host server 120 receives local audio files from all local agents/users who have authorized participation. The host server 120 may construct a single audio playback order for segments of audio within each local audio file by synchronizing the audio segments from the local audio files in chronological order. The host server 120 may perform audio processing to create a single audio playback order/queue (i.e., combined speech from all received local audio files) based on timestamp data in the plurality of local audio files...Each user may have their own record in the DB and each audio segment may be identified with a timestamp. Furthermore, the host server may generate ordered playback information for each of the audio segments from a teleconference involving multiple users based on a chronological order of the audio segments. The ordered playback information may be stored in the database in association with the conference ID, a user ID, or the like... even if there is some overlap between two audio segments of two different users during the live teleconference, the host server 120 can see to it that there is no overlap when it generates the queue for playing back the audio. To do so, the host server 120 may modify an actual timing of an audio segment such that it does not overlap with an actual timing of a previous audio segment).
Claim 16:
De Angelis, by itself, does not seem to completely teach generating, by the one or more processors, a unique sequence value for each electronic message stored on the database based on the respective metadata associated with each electronic message.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches generating, by the one or more processors, a unique sequence value for each electronic message stored on the database based on the respective metadata associated with each electronic message (page 16: “the standard title for chat files will be: type of chat...name of the channel or person...the participants...and date”).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have a unique file name for each generated file.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 17:
De Angelis, by itself, does not seem to completely teach determining, by the one or more processors, whether an electronic message stored on the database is a duplicate message based on the unique sequence value; and upon determining that an electronic message is a duplicate message, removing the duplicate message from the database.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches determining, by the one or more processors, whether an electronic message stored on the database is a duplicate message based on the unique sequence value; and upon determining that an electronic message is a duplicate message, removing the duplicate message from the database (page 2: “auto-sync & archive means that Onna will perform a full sync first and will continuously add any new files generated at the data source”; the process of synchronization includes continuously adding new files after doing a full synch, which would inherently involved removal of any duplicate messages added during the full synchronization of all messages to ensure only new files are added).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have a unique file name for each generated file.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 18:
De Angelis, by itself, does not seem to completely teach the electronic message data comprises edit history information associated with each electronic message.
The Examiner maintains that these features were previously well-known as taught by Sears.
Sears teaches the electronic message data comprises edit history information associated with each electronic message (pages 17-18: “if you have keep everything as a setting across public channels, and direct messages in your workspace...you will be able to see edited and deleted messages in Onna...Onna also started adding “has deletions” or “has edits” on conversations that have had deletes or edits. You can easily search for conversations that have been modified by searching “has edits” or “has:deletions”).
De Angelis and Sears are analogous art because they are from the same problem-solving area, storing messages of a conversation between users and providing the ability to export the stored messages.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of De Angelis and Sears before him or her, to combine the teachings of De Angelis and Sears. The rationale for doing so would have been to have an accurate representation of all messages present in the database.
Therefore, it would have been obvious to combine De Angelis and Sears to obtain the invention as specified in the instant claim(s).
Claim 19:
De Angelis discloses wherein the one or more of the conversational HTML file, the conversational text file, the CSV file associated with each user, the CSV file containing each electronic message and respective metadata associated with each electronic message, or the CSV file associated with each channel or group, are viewable and editable using standard word processing software (0056: The text file can be helpful to a user listing to the combined audio because it can provide additional clarity. In some embodiments, the method may further include performing post-conversation processing on the converted text to remove words that are not of interest when generating the single combined text file to make the text easier and more compact to read).
Note
The Examiner cites particular columns, line numbers and/or paragraph numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. See MPEP 2123.
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 extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED H ZUBERI whose telephone number is (571)270-7761. The examiner can normally be reached Mon – Th 10AM-8PM.
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/MOHAMMED H ZUBERI/Primary Examiner, Art Unit 2178
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