DETAILED ACTION
Examiner’s Remarks
As a preliminary matter, Examiner notes that the instant application was previously examined by a different examiner. As such, Examiner proceeds with prosecution giving full faith and credit to the search and action of the previous examiner per MPEP § 704.01. After reading and considering Applicant’s remarks submitted on 11/23/2025, Examiner has withdrawn the 101 rejection in light of the newly added limitations to the independent claims since they are meaningful limitations that integrate the judicial exception into the practical application of identifying and transmitting suggested recipients over electronic devices.
Response to Arguments
Applicant’s arguments with respect to newly added claim limitation of wherein the additional suggested recipient is suggested when a confidence score associated with the additional suggested recipient is above a predetermined threshold has been considered but is 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 by Applicant’s argument in Applicant’s Remarks submitted on 11/23/2025.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/23/2025 has been entered.
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.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claims 1-7, 10-17 and 20-24 are rejected under 35 U.S.C. 103 as being unpatentable over Eatough in view of Oliveira, Andrew et al., U.S. Patent No. 11611527 (“Oliveira”) and in view of Mummidi US 2020/0344183 Al (“Mummidi”)
Regarding claim 1, Eatough teaches:
A method comprising: receiving an electronic message that is input via a user interface of a device (Eatough, paragraph 0023, “Figure 3 is a block diagram illustrating components of the recipient suggestion system in some embodiments. The recipient suggestion system 300 includes a document store 301, a profile store 302, and an index 303. The recipient suggestion system also includes an indexer 304, a suggest user interface component 305 [user interface of a device], a search recipients component 306, a suggest recipients component 307, and a field suggest component 308.The recipient suggestion system may interface with an electronic mail [electronic message] system 310 or may be implemented as part of an electronic mail system. The document store contains the documents of the corpus.”; (e.g., electronic mail messages (i.e. a message) of a user)).
providing at least a portion of the electronic message to a machine learning network; receiving from the machine learning network, in response to the machine learning network processing at least the portion of the electronic message, an additional suggested recipient for the electronic message (Eatough, paragraph 0021, “In some embodiments, the recipient suggestion system [machine learning network] may be used by an organization that receives electronic communications [electronic message] from external parties to route [receiving from the machine learning network] the electronic communications to parties internal to the organization. For example, when an electronic mail message is received by an organization, the recipient suggestion system may be used to identify similar electronic mail messages [the machine learning network processing at least the portion of the electronic message] and suggest the recipients [an additional suggested recipient for the electronic message] of those electronic mail messages as recipients for the received electronic mail message The recipient suggestion system may also automatically forward the received electronic mail message to the suggested recipients.”).
determining a preferred communication modality for each recipient of the electronic message; (Eatough, col. 5:5 - 32, “The intelligent message router 105 also accesses a participant rules database 135. The participant rules database 135 includes rules and/or preferences specific to the individual participant 260 [for each recipient of the electronic message]. Some of the rules and/or preferences are set by the participant 260. Some of the rules and/or preferences may be based on observations of previous interactions with the participant 260. For example, the participant rules and/or preferences can include, but are not limited to, preferred contact channel (SMS messages preferred to messages transmitted through an app), preferred contact times (after work), contact frequency, and/or other preferences. The intelligent message router 105 compares the message type and information to the participant rules and/or preferences to determine how and if the message is to be transmitted to the participant 260 [determining a preferred communication modality]. In some embodiments, the intelligent message router 105 delays the transmission of the message to an appropriate time. For example, the intelligent message router 105 may determine that the participant 260 only wants to be contacted outside of first shift business hours. The intelligent message router 105 can delay transmission of the message until the appropriate time. In another example, the intelligent message router 105 may determine that the participant 260 only wants to be contacted 2 times a week. The intelligent message router 105 may then determine that the participant 260 has already been contacted twice this week. The intelligent message router 105 then determines whether the message is to be saved for later or dropped completely.”).
outputting a notification associated with the electronic message, [wherein the notification indicates the preferred communication modality for each recipient and] allows the additional suggested recipient to be added to as a recipient of the electronic message before the electronic message is transmitted (Eatough, paragraphs 0003, 0005, and 0021, “If a name entered by the sender in a to-field cannot be resolved to a single entity (e.g., a contact or a distribution list) [recipient], electronic mail systems may display a list of possible entities [outputting a notification associated with the message] that might be the intended entity…. 0005 The system receives an indication of the target document [the electronic message]. The system identifies documents that are similar to the target document based on a comparison of document data of the target document to document data of documents in a corpus of documents. The system then identifies entities associated with the identified documents. The system then suggests that one or more of the identified entities be considered as recipients [outputting a notification associated with the electronic message], as suggested recipients to be considered) for the target document. [the additional suggested recipient to be added to as a recipient of the message before the message is transmitted]; … 0021 In some embodiments, the recipient suggestion system [machine learning network] may be used by an organization that receives electronic communications from external parties to route [receiving from the machine learning network] the electronic communications to parties internal to the organization. For example, when an electronic mail message is received by an organization, the recipient suggestion system may be used to identify similar electronic mail messages [the machine learning network processing at least the portion of the electronic message] and suggest the recipients [an additional suggested recipient for the electronic message] of those electronic mail messages as recipients for the received electronic mail message The recipient suggestion system may also automatically forward the received electronic mail message to the suggested recipients [the additional suggested recipient to be added to as a recipient of the electronic message before the message is transmitted].”).
in response to receiving via the user interface of the device, a selection of the additional suggested recipient, adding the additional suggested recipient to the electronic message; and transmitting the electronic message. (Eatough, paragraphs 0021 and 0026, fig. 4, “Figure 4 is a flow diagram that illustrates processing of the suggest user interface component of the recipient suggestion system in some embodiments. The suggest user interface component 400 is passed an indication of a document and suggests recipients to a sender of the document. In block 401, the component invokes a suggest recipients component to identify recipients to suggest to the sender. In block 402, the component selects the top-ranked suggested recipients returned by the suggest recipients component. In block 403, the component displays area [receiving via the user interface of the device] the names of the suggested recipients (e.g., people or distribution lists) in the suggestion [a selection of the additional suggested recipients]. In decision block 404, if the sender requests more information about a suggested recipient, then the component continues at block 405, else the component continues at block 406.); (0026 In block 407, the component adds the suggested recipient as a current recipient and then loops to block 401 to suggest additional recipients [adding the additional suggested recipient to the electronic message]); … 0021 In some embodiments, the recipient suggestion system may be used by an organization that receives electronic communications from external parties to route the electronic communications to parties internal to the organization. For example, when an electronic mail message is received by an organization, the recipient suggestion system may be used to identify similar electronic mail messages and suggest the recipients of those electronic mail messages as recipients for the received electronic mail message. The recipient suggestion system may also automatically forward [transmitting the electronic message] the received electronic mail message to the suggested recipients”).
Eatough does not explicitly teach [and outputting a notification associated with the electronic message,] wherein the notification indicates the preferred communication modality for each recipient and [allows the additional suggested recipient to be added to as a recipient of the electronic message before the electronic message is transmitted].
Oliveira teaches [and outputting a notification associated with the electronic message,] wherein the notification indicates the preferred communication modality for each recipient and [allows the additional suggested recipient to be added to as a recipient of the electronic message before the electronic message is transmitted] (Oliveira, col. 5:33 - 50, “If the intelligent message router 105 determines that the message is to be transmitted, a message generator 140 generates the message for transmission. The message generator 140 receives the participant information, participant preferred message channel, the message type, and the payload information. Then the message generator 140 generates the message for transmission on the desired message channel. [wherein the notification indicates the preferred communication modality for each recipient] For example, the message could include, but it not limited to, a text message, an SMS message, a push message through an app, a chat message, a website based chat message, a push message for a specific type of phone, a message on a messaging application, an automated phone call, an email, a direct message, and/or any other type of message. In some embodiments, the message generator 140 uses a template to generate the messages, where the message generator 140 has access to a plurality of templates, such as those for a plurality of different channels and a plurality of different message types.”).
In view of the teachings of Oliveira it would have been obvious for a person of ordinary skill in the art to apply the teachings of Oliveira to Eatough before the effective filing date of the claimed invention in order to reduce the amount of message and size of messages required to send a message (cf. Oliveira, col. 4:30 - 39, “More specifically, the event information can identify the message and participant 260 that the message is directed to. The information about that participant 260 is retrieved from the participant information database 120, while the payload for the message is retrieved from the payload information database 125. This reduces the amount of messages and size of messages for communicating the event information, since the payload doesn’t need to be transmitted through the event receiver 115 multiple times, or even once. Only the payload identifier is needed.”).
Eatough in view of Oliveira does not explicitly teach wherein the additional suggested recipient is suggested when a confidence score associated with the additional suggested recipient is above a predetermined threshold
However, Mummidi teaches:
wherein the additional suggested recipient is suggested when a confidence score associated with the additional suggested recipient is above a predetermined threshold(Mummidi, para., [0123], see also fig. 4, “The score may be calculated based on a plurality of factors which can include the identities of the communication participants. Thus, the identities of the drafter and/or any other recipients[wherein the additional suggested recipient] of the message may represent one of multiple factors used to assign a score to the message...[t]he score may be compared to a threshold value and determining that the score exceeds the threshold value may cause the system to communicate the auto-response notice[is suggested when a confidence score associated with the additional suggested recipient is above a predetermined threshold].” ).
In view of the teachings of Mummidi it would have been obvious for a person of ordinary skill in the art to apply the teachings of Mummidi to Eatough in view of Oliveira before the effective filing date of the claimed invention in order to better effectively identify the right individuals to communicate with based on the purpose of the message(Mummidi, para., 0007, “[A] system can generate an auto-response notice based on one or more characteristics of
the message and on the organizational change of a particular recipient. The characteristics may be analyzed to determine if the content or purpose of the message is related to a former
group of the recipient. One technique for the system to classify a message as being related to a former group is scoring the message according to data contained within the message. Data from outside the message that provides context for the data contained within the message may also
be used for scoring. Scoring may be implemented by comparing the score assigned to a message with a threshold and identifying the message as being related to a former group if the score exceeds the threshold.” ).
Regarding claim 2 and analogous claims 12 and 21, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 1.
Eatough further teaches:
wherein the portion of the electronic message comprises a body of the electronic message (Eatough, paragraph 0019, fig. 1, “Figure 1 illustrates a display page of an electronic mail system with suggested recipients based on document data [contextual information] in some embodiments. Display page 100 includes a to-field 101 [contextual information], a subject-field 102, an attachmentfield 103, a content-field 104 [body of the electronic message], and a suggestion area 105.”).
wherein processing at least the portion of the electronic message comprises extracting contextual information associated with content included in the body of the electronic message (Eatough, paragraph 0019, fig. 1, “Figure 1 illustrates a display page of an electronic mail system with suggested recipients based on document data [contextual information] in some embodiments. Display page 100 includes a to-field 101 [contextual information], a subject-field 102 ([contextual information], an attachmentfield 103, a content-field 104 [body of the electronic message], and a suggestion area 105. The to-field represents a prompt for recipients, the subject-field contains the subject of the electronic mail message, and the attachment-field contains the name of an attached document. The content-field contains the text of the electronic mail message [content included in the body of the electronic message]. The suggestion area displays suggested recipients as identified by the recipient suggestion system. As the user enters the subject and content and attaches documents, the recipient suggestion system may identify electronic mail messages that have similar subjects, content, and attachments and suggest parties [additional suggested recipient] to those identified electronic mail messages as recipients. The recipient suggestion system may dynamically [processing] update the list suggested recipients as the user enters the subject and content and attaches documents.)”).
and wherein the additional suggested recipient is selected based at least in part on the contextual information. (Eatough, paragraphs 0019 and 0023, “The suggestion area displays suggested recipients as identified by the recipient suggestion system. As the user enters the subject and content and attaches documents, the recipient suggestion system may identify electronic mail messages that have similar subjects, content, and attachments and suggest parties [additional suggested recipient] to those identified electronic mail messages as recipients. The recipient suggestion system may dynamically [processing] update the list suggested recipients as the user enters the subject and content and attaches documents … 0023, The suggest recipients component identifies suggested recipients [the additional suggested recipient is selected based at least in part on the contextual information] based on similarity of the parties, subjects, attachments, and/or content of documents in a document corpus to the document data [contextual information] of a target document and ranks the suggested recipients.”; Examiner notes subject, content and attachments are document data (i.e. contextual information)).
Regarding claim 3 and analogous claims 13 and 22, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 2.
Eatough further teaches wherein the contextual information comprises mentioning a name of the additional suggested recipient. (Eatough, paragraphs 0016-0017, “In some embodiments, a recipient suggestion system suggests recipients based on their association with documents that are similar to a target document. To suggest recipients, the recipient suggestion system receives an indication of a target document. For example, the target document may be a target electronic mail message. The recipient suggestion system compares document data of the target document with the document data of documents in a corpus of documents to identify documents that are similar to the target document. For example, the recipient suggestion system may compare the content of the target electronic mail message to the content of electronic mail messages that the sender has sent or received. The recipient suggestion system then identifies entities associated with the identified documents that are similar. For example, the entities associated with a similar electronic mail message may be the parties to the electronic message as identified in the from-field, to-field, ccfield, and bcc-field. In the case of a document that is not an electronic mail message, the associated entities may include the authors, editors, reviewers, and readers of the document. The recipient suggestion system then suggests that the identified entities be considered as recipients of the target document.; … 0017 In some embodiments, the recipient suggestion system allows a user to enter a generalized recipient query in a recipient field, conducts a people finder search to identify people that match the recipient query [the contextual information comprises mentioning a name of the additional suggested recipient], and suggests those people as recipients. The recipient suggestion system may prompt the user for entry of a recipient of a target electronic communication. For example, the recipient suggestion system may prompt the user by displaying a to-field of an electronic mail message. The recipient suggestion system then receives a response to the prompt such as the entry of the name of the recipient (e.g., Jane Doe) or a recipient query (e.g., “Board of Directors” or “Jane Doe’s assistant] [the contextual information comprises mentioning a name of the additional suggested recipient]. The recipient suggestion system may first attempt to determine whether the response matches an entity in the user’s address book. If it does, the recipient suggestion system resolves the response to that entity. If it does not, the recipient suggestion system submits the response as a people query to a people finder search engine. A people finder search engine may search various information sources to identify people who match the people query.”; Examiner notes entities associated with similar documents are part of document data, (i.e. contextual information)).
Regarding claim 4 and analogous claims 14 and 23, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 1.
Eatough further teaches:
wherein the portion of the electronic message comprises an attachment to the electronic message. (Eatough, Page 5, claim 4, “wherein the document data is selected from the group consisting of entities associated with the document, content of the document, subject of the document, title of the document, and attachment to the document [wherein the portion of the electronic message comprises an attachment to the electronic message]”).
wherein processing at least the portion of the electronic message comprises analyzing the attachment (Eatough, paragraph 0022, “In some embodiments, the recipient suggestion system may use various techniques for assessing [analyzing] the similarity between documents … For example, similarity between the subject of electronic mail messages may be weighted higher than similarity between content of the electronic mail messages. Generally, the recipient suggestion system generates subscores for similarity derived from similar parties (p), subjects (s), attachments (a) [analysis of the “attachment], and content (b) as represented by the following equation: where sr represents the score for document r, ~ represents the weight for sub-score x, and s; represents the sub-score for x.)”).
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and determining other users associated with the attachment and wherein the additional suggested recipient is selected based at least in part on the other users associated with the attachment. (Eatough, paragraph 0023, “The suggest recipients component identifies suggested recipients [determining other users associated with the attachment and wherein the additional suggested recipient is selected] based on similarity of the parties, subjects, attachments [based at least in part on the users associated with the attachment), and/or content of documents in a document corpus to the document data of a target document and ranks the suggested recipients.”).
Regarding claim 5 and analogous claims 15 and 24, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 1.
Eatough further teaches:
wherein the portion of the electronic message comprises one or more recipients of the electronic message (Eatough, paragraph 0016, “For example, the recipient suggestion system may compare the content of the target electronic mail message to the content of electronic mail messages that the sender has sent or received. The recipient suggestion system then identifies entities associated with the identified documents that are similar. For example, the entities associated with a similar electronic mail message may be the parties to the electronic message as identified in the from-field, to-field, cc-field, and bcc-field [wherein the portion of the electronic message comprises one or more recipients of the electronic message]. In the case of a document that is not an electronic mail message, the associated entities may include the authors, editors, reviewers, and readers of the document [wherein the portion of the message comprises one or more recipients of the electronic message]. The recipient suggestion system then suggests that the identified entities be considered as recipients of the target document.”).
and wherein processing at least the portion of the electronic message comprises determining the additional suggested recipient based on the one or more recipients of the electronic message. (Eatough, paragraphs 0022 - 0023, “In some embodiments, the recipient suggestion system may use various techniques for assessing the similarity between documents …For example, similarity between the subject of electronic mail messages may be weighted higher than similarity between content of the electronic mail messages. Generally, the recipient suggestion system generates sub-scores for similarity derived from similar parties (p) [one or more recipients of the message], subjects (s), attachments (a), and content (b) as represented by the following equation: where sr represents the score for document r, ~ represents the weight for sub-score x, and s; represents the sub-score for x. … 0023 line 15-18, The suggest recipients component identifies suggested recipients [determining the additional suggested recipient] based on similarity of the parties [one or more recipients of the message], subjects, attachments, and/or content of documents in a document corpus to the document data of a target document and ranks the suggested recipients.”).
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Regarding claim 7 and analogous claim 17, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 1.
Eatough further teaches:
wherein the portion of the electronic message comprises a user profile associated with the device (Eatough, paragraphs 0001 and 0023, “The sender [user] of such an electronic communication typically needs to enter the full electronic mail address (e.g., “Jane.Doe@acme.com”) of each recipient. Most electronic mail systems provide address stores (e.g., address books or contact lists) [a user profile associated] that map the names of contacts to their electronic mail addresses. … 0023 The recipient suggestion system may interface with an electronic mail system 310 or may be implemented as part of an electronic mail system. The document store contains the documents of the corpus (e.g., electronic mail messages of a user). The profile store [user profile] contains profiles of people associated with an organization.”).
and wherein processing at least the portion of the electronic message comprises determining the additional suggested recipient based on the user profile associated with the device. (Eatough, paragraph 0017, “The recipient suggestion system may prompt the user for entry of a recipient of a target electronic communication. For example, the recipient suggestion system may prompt the user by displaying a to-field of an electronic mail message. The recipient suggestion system then receives a response to the prompt such as the entry of the name of the recipient (e.g., Jane Doe) or a recipient query (e.g., “Board of Directors” or “Jane Doe’s assistant”) [determining the additional suggested recipient]. The recipient suggestion system may first attempt to determine whether the response matches an entity in the user’s address book [based on the user profile associated with the device”). If it does, the recipient suggestion system resolves the response to that entity.”).
Regarding claim 10, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 1.
Eatough further teaches wherein the confidence score is determined based at least in part on a comparison of at least the portion of the electronic message to profile information of one or more contacts associated with a user profile associated with the device. (Eatough, paragraphs 0022-0023, figs. 3 and 4, “Figure 3 is a block diagram illustrating components of the recipient suggestion system in some embodiments. The recipient suggestion system 300 includes a document store 301, a profile store 302, and an index 303. The recipient suggestion system also includes an indexer 304, a suggest user interface component 305 [the device], a search recipients component 306, a suggest recipients component 307, and a field suggest component 308. The recipient suggestion system may interface with an electronic mail system 310 or may be implemented as part of an electronic mail system. The document store contains the documents of the corpus (e.g., electronic mail messages of a user). The profile store contains profiles of people associated with an organization [one or more contacts associated with a user profile]…. The suggest recipients component identifies suggested recipients based on similarity of the parties, subjects, attachments, and/or content of documents in a document corpus to the document data of a target document and ranks the suggested recipients. The field suggest component is passed an indication of the field and identifies similar documents based on that field and then generates a sub-score for the field for each of the entities associated with those similar documents.). … 0022 For example, the index may map sequences of ncharacters to the documents that contain those sequences. The recipient suggestion system may also weight scores generated based on different types of document data. For example, similarity between the subject of electronic mail messages may be weighted higher than similarity between content of the electronic mail messages. Generally, the recipient suggestion system generates sub-scores for similarity derived from similar parties (p), subjects (s), attachments (a), and content (b) as represented by the following equation: where Sr represents the score for document r, Wx represents the weight for sub-score x, and s; represents the sub-score for x.”; Examiner notes this score reflects the confidence that a particular entity is relevant as claimed the confidence information, or both is determined based at least in part on a comparison of at least the portion of the message to profile information of one or more contacts associated with a user profile associated with the device. Different types of document data are used to generate scores and sub-scores for similarity including profile information of one or more contacts associated with a user profile and are “compared” for similarity. The score reflects the confidence that a particular document is relevant).
Regarding claim 11, Eatough teaches A device comprising: a processor; [[and]] memory in electronic communication with the processor; and instructions stored in the memory, the instructions being executable by the processor to: (Eatough, paragraph 0024, “The computing devices and systems on which the recipient suggestion system may be implemented may include a central processing unit [a processor], input devices, output devices (e.g., display devices and speakers), storage devices ( e.g., memory and disk drives) [memory], network interfaces, graphics processing units, accelerometers, cellular radio link interfaces, global positioning system devices, and so on.”; The remaining claim limitations of claim 11 have analogous limitations of claim 1 and is rejected under the same rationale).
Regarding claim 20, Eatough teaches A non-transitory, computer-readable medium comprising a set of instructions stored therein which, when executed by a processor, causes the processor to: (Eatough, paragraph 0024, “The computing devices may access computer-readable media that includes computer-readable storage media and data transmission media. The computer-readable storage media are tangible storage means that do not include a transitory, propagating signal. Examples of computer-readable storage media include … memory such as primary memory, cache memory, and secondary memory (e.g., DVD) and include other storage means. The computer-readable storage media may have recorded upon or may be encoded with computer-executable instructions or logic that implements the recipient suggestion system.”; The remaining claim limitations of claim 20 have analogous limitations of claim 1 and is rejected under the same rationale).
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Eatough, as modified by Oliveira, in view of Mummidi, and further in view of Keohane, et al., Pre-Grant Publication No. US 2008/0104175 (“Keohane”).
Regarding claim 6 and analogous claim 16, Eatough, as modified by Oliveira and Mummidi, teaches the method of claim 5.
Eatough, as modified by Oliveira and Mummidi, does not explicitly teach:
further comprising: determining a recipient of the one or more recipients of the electronic message is out of office; and
determining the additional suggested recipient based on a rule for messages to be sent to the additional suggested recipient.
Keohane teaches:
further comprising: determining a recipient of the one or more recipients of the electronic message is out of office; and
(Keohane, paragraph 0046, fig. 4A, “FIG. 4A illustrates the process of providing a reminder notification to a sender of email when executing Out-of-Office utility 136 along with email utility 137, according to the described embodiment. The process begins at block 401, at which Out-of-Office utility 136 detects the receipt of an automated out-of-office reply. [determining one of the one or more recipients of the electronic message is out of office; and] The automated out-of-office reply is received by a user (sender) when the recipient (of sender’s email) has activated the out-of-office email reply feature. Out-of-Office utility 136 stores the data from the automated out-of-office reply, as shown at block 402.”).
determining the additional suggested recipient based on a rule for messages to be sent to the additional suggested recipient.
(Keohane, paragraph 0049, “Returning to block 412, if the user override is not detected, indicating that the user intends to make some adjustment to the recipient addresses, the out-of-office utility facilitates the entry of the backup recipient’s address and other user selectable addressing and emailing options, as shown at block 413. One possible option is for the user to replace the original (out-of-office) recipient’s address with the backup recipient address. [determining the additional suggested recipent based on a rule for messages to be sent to the additional suggested recipient] Another option is for the sender/user to add the backup recipient’s address along with the original recipient’s address. In one embodiment, either option may be facilitated by the selection of the backup recipient address (User3) within the reminder message 305, where the selection automatically populates the address field with the backup recipient address. Yet another option is for the sender to cancel the email completely, where the sender only wishes to send the email to the out-of-office recipient and may decide to wait until the out-of-office recipient returns. Once the sender has made the required changes and the out-of office utility detects the selection of the send button of email GUI 300, the email engine is triggered to send the email to the email IDs within the address field, as shown at block 414.”).
In view of the teachings of Keohane it would have been obvious for a person of ordinary skill in the art to apply the teachings of Keohane to Eatough as modified by Oliveira and Mummidi before the effective filing date of the claimed invention in order to save time by automatically sending a message to a backup person when the recipient is out of office (cf. Keohane, paragraphs 0007 - 0008, “[0007] With the present out of office notification function, the sender often does not remember the recipient’s return date or may not be given a return date, and the sender may periodically send an email to the recipient, only to receive a new out of office notification. This is particularly true when a recipient has set the out-of-office function for an extended period of time. If the sender has time-sensitive communication that must be addressed and there is a second or backup person (other then the out-of-office recipient) who is capable of responding to the sender’s email request, the sender may lose valuable time through the redundant actions of resending and repeatedly receiving multiple out-of-office notifications before taking appropriate action. The present invention appreciates the importance of a method to facilitate an out-of-office aware e-mail system that gives the sender the opportunity to reduce redundancy and increase efficiency while the sender carries out email messaging activities.”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sofershtein, Zvi, and Sara Cohen. "Predicting email recipients." Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015. 2015(details a method of accurately predicting potential suggested recipients of a message based upon various features of the message)
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/Adam C Standke/
Primary Examiner
Art Unit 2129